Synthetic transcription factor and uses thereof

ABSTRACT

The present invention provides for a synthetic transcription factor (TF) comprising a first peptide capable of binding a target ligand, a second peptide capable of binding a target DNA, and a peptide linker linking the first and second peptides. The present invention also provide for a system for modulating the mutagenesis frequency of a host cell. The host cell has a mutator rate (R) which is inversely proportional to a phenotypic trait (P).

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority as a continuation application of PCTInternational Patent Application No. PCT/US13/74214, filed Dec. 10,2013, which claims priority to U.S. Provisional Patent Application Ser.No. 61/735,507, filed Dec. 10, 2012, both of which are herebyincorporated by reference in their entireties.

STATEMENT OF GOVERNMENTAL SUPPORT

The invention described and claimed herein was made utilizing fundssupplied by the U.S. Department of Energy under Contract No.DE-AC02-05CH11231. The government has certain rights in this invention.

FIELD OF THE INVENTION

The present invention is in the field of gene expression.

BACKGROUND OF THE INVENTION

The complexity inherent in biological systems challenges efforts torationally engineer novel phenotypes, especially those not amenable tohigh-throughput screens and selections. In nature, adaptation canrapidly evolve new traits by changing the mutation rate in a cell.

Adaptation is a behavior that allows cells to survive and thrive inconstantly changing environmental conditions. This behavior ischaracterized by rapid genetic change creating rare beneficialmutations¹. The appearance of microbial strains with higher than averagemutation rates accompany periods of adaptation in both natural andlaboratory environments²⁻⁴. Models and experimental data of the adaptiveprocess indicate a variable mutation rate strategy is used to evolvetraits, where increased mutation rates are only beneficial topopulations with low phenotypic diversity, while populations with highdegrees of diversity benefit from decreased mutation rates⁵⁻⁷.

Many mutagenesis strategies to generate diversity in the laboratoryexist, but most industrially-important phenotypes are not amenable tothe high-throughput screens and selections required to isolate mutantsexhibiting the desired traits^(8,9). Furthermore, directed evolutionstrategies that generate mutant libraries in vitro are limited by thetransformation efficiency of the cell, and those that use mutatorstrains demonstrating unregulated high mutation rates to generate mutantlibraries in vivo¹⁰ suffer from the accumulation of deleteriousmutations that eventually lead to cell death. Although adaptation hasproven useful for evolving certain phenotypes, its application islimited to traits that are directly tied to growth¹¹. Therefore, amethod capable of regulating mutagenesis in vivo according to aparticular phenotype, independent of whether it is linked to growth,could circumvent the constraints set by transformation inefficiencies,deleterious mutations, and assay availability.

SUMMARY OF THE INVENTION

The present invention provides for a synthetic transcription factor (TF)comprising a first peptide capable of binding a target ligand, a secondpeptide capable of binding a target DNA, and a peptide linker linkingthe first and second peptides. In some embodiments, the target DNA is anactivator or repressor site of a gene of interest. Depending on thetarget DNA and the gene of interest, the binding of target DNA by thesynthetic TF can either activate or repress transcription of the gene ofinterest from a target promoter.

The present invention provide for a system for modulating themutagenesis frequency of a host cell. The host cell has a mutator rate(R) which is inversely proportional to a phenotypic trait (P). The hostcell comprises a sensor module and a mutator module. The sensor modulecomprises a target ligand, a TF (such as a synthetic TF) that binds thetarget ligand, and a target promoter regulated by the TF. The mutatormodule comprises the target promoter operably linked to a gene thatincreases mutation rate (mutator or mutator gene) of the host cell. Thesystem comprises a host cell comprising a synthetic TF, a target DNAwhich the binding thereof modulates the expression of the gene thatincreases mutation rate of the host cell.

The present invention also provides for a genetically modified host cellcomprising the synthetic TF or system useful for the methods of thepresent invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing aspects and others will be readily appreciated by theskilled artisan from the following description of illustrativeembodiments when read in conjunction with the accompanying drawings.

FIG. 1. Design of Synthetic Transcription Factor (TF). Part1 is aprotein or protein domain (e.g., ligand-binding domain of a natural TF)that binds the target ligand, Part2 is an activation or DNA-bindingdomain, and Part3 is a DNA sequence fusing together Part1 and Part2.

FIG. 2. Sensor module with chimeric protein IA consisting of Idi asPart1 AraC's DNA-binding domain as Part2, and AraC's linker sequence asPart3. One model for how IA regulates P_(BAD) is IA binds the DNAsequence I₁I₂, activating transcription from P_(BAD) in the absence ofIPP (left), and IPP-bound IA dimerizes, preventing activation of P_(BAD)(right).

FIG. 3. Output of four sensor modules each with a different IA variantto changing IPP concentrations in E. coli HC175 monitored with mcherry.Diamonds represent AC, triangles IA32, squares IA, and circles IA44.

FIG. 4. Sensor module for detecting IPP in S. cerevisiae. The syntheticTF is a chimeric protein of Idi as Part1 and either Gal4's AD or DBD asPart2. Part3 is a synthetic DNA sequence we designed to fuse Part1 andPart2 together. One model for P_(GAL10) regulation is Idi dimerizes whenIPP bound, bringing the upstream activation sequence (UAS) bound Gal4DBD in close enough proximity with the Gal4 AD to activate transcription(left). In the absence of dimerization at the LBD, there is notranscription from P_(GAL10) (right).

FIG. 5. Output of three sensor modules for IPP with synthetic TFs andP_(GAL10) in S. cerevisiae is monitored with yEcitrine. The syntheticTFs consisted of Idi, Idi1, or Erg20 as the LBD fused to either Gal4'sAD or DBD. “Ctl” is the control synthetic TFs. The sensor modules weretested in S. cerevisiae MO219.

FIG. 6. Logic gate representation of synthetic algorithm illustrating Pand R are inversely related, and a feedback loop (dotted line) from R toP shows R can affect P.

FIG. 7. (Top) Three membership functions (L, M, and H representing low,medium, high states, respectively) for describing the inputs and outputof the FREP algorithm. The inputs are phenotypic diversity related tothe trait being evolved (P) and attenuation (A), and the output is themutation rate (R). A is a constraint on the maximum value for R andtunes P's effect on R. (Bottom) Rule table for relating input to output.Rules are listed as “IF [P] AND [A] THEN [R]” using the input and outputstates as descriptors. For example, the rule at the bottom-right cornerstates “IF P (phenotypic diversity) is high AND A (attenuation) is highTHEN R (mutation rate) is low”.

FIG. 8. Implementation of FREP using a sensor and mutator module. Thesensor module converts the inputs A and P into a transcriptional level,which the mutator module converts to R. A constrains the strength anddynamics of the transcriptional output. R affects P, creating a feedbackloop between the two modules.

FIG. 9. FREP implemented with sensor module P_(aroF3) and mutator modulemutD5. P_(aroF3) consists of tyrosine, modified TyrR, and modifiedP_(aroF); the mutator module consists of mutD5. TyrR dimers activatetranscription from P_(aroF) in the absence of tyrosine (top), andtyrosine-bound TyrR form hexamers that dimerize to repress transcriptionfrom P_(aroF) (bottom).

FIG. 10. Tyrosine production from ten mutants evolved with FREP showingthe lowest fluorescence after 24 hours. C is the control not evolvedwith FREP.

FIG. 11. Ten mutants showing the lowest fluorescence after 24 hours ofFREP with mutD5 controlled by IA44 were transformed with pLyc, andlycopene production was quantified. C is the control that did notundergo FREP. Lycopene production is presented as p.p.m. (ug/g dry cellweight).

FIG. 12. Lycopene production sampled every 48 hours from E. coli MG1655expressing pLyc, sensor module, and mutator module over 288 hours. Thetranscription factors used in the sensor module were AraC (black bars),IA32 (dark gray bars), or IA44 (light gray bars). Lycopene production ispresented as p.p.m. (ug/g dry cell weight). Sensor modules with AraCwere induced with 10 mM arabinose.

FIG. 13. FREP design. (a) FREP implementation of the variable mutationstrategy using an adaptive control system. The sensor controls thechange in transcriptional level (ΔT) in the system. The actuatorconverts the transcriptional level (T) into a mutation rate (M) thatmodifies the genome to produce the target phenotype gauged by L. As Lincreases, the sensor increases ΔT, which causes the actuator todecrease M. (b) Two different outcomes of FREP are possible depending onwhether the ligand is permeable to the cell membrane. Circles representthe concentration of ligand in the cell. If the ligand is permeable tothe membrane, then a few or a single, high-level producer of L couldreduce M in all other cells, causing the entire population to stopevolving independent of each cell's level of L (top). If the ligand isnot permeable to the membrane, then each cell in the population evolvesindependently of the other cells (bottom).

FIG. 14. FREP evolves increased tyrosine production. (a) Out of twentysensors tested, the most sensitive sensors for each promoter (P_(aroF),P_(aroL), P_(aroP)) are compared for sensitivity to changes in tyrosineconcentration in vivo. Bars represent tyrosine production and ♦represent relative fluorescence units normalized to OD measured at 600nm DJ106 and DJ166 are variants of E. coli BLR, and DJ166 produces moretyrosine than DJ106. (b) Tyrosine production from ten mutants evolvedwith FREP showing the lowest fluorescence after 24 hours. C is thecontrol not evolved with FREP.

FIG. 15. Synthetic transcription factors (TFs) respond to IPP. (a) Asynthetic TF consists of 3 parts: Part1 binds the target ligand, Part2converts the binding signal into a change in RNA polymerase binding tothe target promoter, and Part3 is an amino acid linker fusing Part1 andPart2 together. Here, a sensor with synthetic TF IA comprised of Idi asPart1 and AraC's DBD and linker as Part2 and Part3, respectively. Onemodel for how IA regulates P_(BAD) is IA binds the DNA sequence I₁I₂,activating transcription from P_(BAD) in the absence of IPP (top), andIPP-bound IA dimerizes, preventing binding to I₁I₂ and activation ofP_(BAD) (bottom). (b) Output of four sensors, each with a different TF,to changing IPP concentrations in E. coli HC175 monitored with mcherry.♦ represent AC, ▴ IA32, ▪ IA, and ● IA44. (c) A sensor for detecting IPPin S. cerevisiae. The synthetic TF consists of Idi as Part1, GAL4's ADand DBD as Part2, and a 19-amino acid linker as Part3. One model forP_(GAL10) regulation is that Idi dimerizes when bound to IPP, bringingthe upstream activation sequence (UAS)-bound GAL4 DBD in close enoughproximity with the GAL4 AD to activate transcription (top). In theabsence of Part1 dimerization, there is no transcription from P_(GAL10)(bottom). (d) P_(GAL10) output from three sensors with synthetic TFs inS. cerevisiae MO219 induced with galactose. The synthetic TFs consist ofIdi, Idi1, or Erg20 as Part1 fused to GAL4's AD and DBD. “Ctl” is thecontrol without synthetic TFs. Output was monitored with the fluorescentprotein yEcitrine and normalized to fluorescence in the absence ofgalactose.

FIG. 16. FREP evolves increased IPP production. Lycopene productionsampled every 72 hours over a 432-hour period from E. coli MG1655expressing pLyc, an IPP sensor, and an actuator. The transcriptionfactors used in the sensor were AraC (black bars), IA32 (dark graybars), or IA44 (light gray bars). Lycopene production is presented asp.p.m. (ug/g dry cell weight). The sensor with AraC was induced with 10mM arabinose.

FIG. 17. FREP design to increase tyrosine production. (a) In one design,the sensor consists of TyrR and P_(aroF), and the actuator consists ofmutD5. TyrR dimers activate transcription from P_(aroF) in the absenceof tyrosine. (b) Tyrosine-bound TyrR form hexamers that dimerize torepress transcription from P_(aroF).

FIG. 18. Fluorescent output from tyrosine sensors using P_(aroF) . E.coli DJ106 and DJ166 with one of seven sensors consisting of thepromoter P_(aroF) and a variant of TyrR were assessed for theirfluorescence output (♦) based on the amount of tyrosine produced (bars).The table lists each sensor with its constituent variant of TyrR andP_(aroF).

FIG. 19. Fluorescent output from tyrosine sensor using P_(aroL) , E.coli DJ106 and DJ166 with one of six sensors consisting of a variant ofthe promoter P_(aroL) and a variant of TyrR were assessed for theirfluorescence output (♦) based on the amount of tyrosine produced (bars).The table lists each sensor with its constituent variant of TyrR andP_(aroL).

FIG. 20. Fluorescent output from tyrosine sensors using P_(aroP) . E.coli DJ106 and DJ166 with one of seven sensors consisting of a variantof the promoter P_(aroP) and a variant of TyrR were assessed for theirfluorescence output (♦) based on the amount of tyrosine produced (bars).The table lists each sensor with its constituent variant of TyrR andP_(aroP).

FIG. 21. EMSA experiments show IA binds DNA. We tested whether IA boundto the DNA duplexes of I₁, I₁I₂, or the sequence from P_(C) to P_(BAD)(20 nM) in vitro. (a) Increasing IA concentrations (0, 2.5, 5, 10 nM)led to increased intensity in shifted bands. (b) IA binding in thepresence (+, 10 μM) and absence (−, 0 μM) of IPP with 10 nM of IA.

FIG. 22. In vitro FRET DNA-binding assay shows IA interacting with DNA.(a) Schema illustrating FRET DNA-binding assay. A DNA duplex is splitinto two half-duplexes, and each half is tagged with either afluorophore (F) or quencher (Q). Fluorescence is detected in the absenceof a protein to bring the two half duplexes together. However, theenergy is transferred from F to Q when the protein binds both halfsequences and brings F in close enough proximity with Q, leading to adecrease in fluorescence. (b) Decreases in fluorescence were observedwhen the I₁ half-duplex (▪, 100 nM; ▴, 200 nM) were incubated withdifferent concentrations of IA (0, 5, 10, and 20 nM). Relativefluorescence values were calculated by subtracting the fluorescencevalue of the negative control without the F label and dividing by thefluorescence value from 0 nM IA.

FIG. 23. In vitro FRET DNA-binding assay shows that IPP affects IAbinding to DNA. We incubated different concentrations of IA with 100 nMof each I₁I₂ labeled DNA half-duplex in vitro. A greater change influorescence was observed with increasing concentrations of IA,consistent with the binding experiment with I₁ half-duplexes assubstrate. The change in fluorescence decreased in the presence of IPP(♦, 500 nM) compared to when no IPP was added (▪, 0 nM).

FIG. 24. Modified IPP sensors exhibit different dynamics 60 differentsensors for IPP were generated by mutating IA using error-prone PCR andmonitoring sensor output from P_(BAD) with mcherry. Output is presentedin relative fluorescence units normalized to OD measured at 600 nm Graybars indicate output in the absence of mevalonate (0 mM), and black barsindicate output in the presence of mevalonate (10 mM). A control sensorwith IA is included on the left.

FIG. 25. Fluorescence output and mutation rate correlate. FREP wasimplemented with the mutD5 mutator and an IPP sensor with one of thefollowing TFs: AC, IA32, or IA44. Fluorescence (▴) represents themaximum fluorescence measured from HC175 in the absence of mevalonatefor each sensor normalized to that with IA44 (FIG. 3B). The mutationrate (▪) was calculated with Luria-Delbruck analysis using rifampicinresistance as the phenotype, analyzed using FALCOR, and the mutationrate for each TF determined by FALCOR was normalized to that determinedfor IA44. The correlation coefficient between measured fluorescence andmutation rate is r=0.97.

FIG. 26. FREP evolved increased IPP in 24 hours. C is the negativecontrol that did not undergo FREP. (a) The effects of dynamic control ofmutation rate was determined by comparing lycopene production from C to10 colonies of E. coli MG1655 after undergoing FREP with IA44 for 24hours. (b) The effects of static control of mutation rate was determinedby comparing lycopene production from C to 10 colonies of E. coli MG1655after undergoing FREP with AraC induced with 10 mM arabinose for 24hours.

FIG. 27. pLyc from mutants do not lead to increased lycopene production.pLyc was isolated from E. coli MG1655 after undergoing FREP for 0, 72,144, 216, 288, 360, and 432 hours. The plasmids were transformed into E.coli MG1655 and lycopene production was quantified.

FIG. 28, A-D. Primer sequences. Sequences of primers (5′ to 3′) used toassemble plasmids in this study. Underlined parts indicate restrictionsites unless otherwise indicated.

FIG. 29. A particular embodiment of the feedback-regulated forcedevolution (FRFE).

FIG. 30. A particular embodiment of the inducible forced evolution(IFE).

DETAILED DESCRIPTION OF THE INVENTION

Before the invention is described in detail, it is to be understoodthat, unless otherwise indicated, this invention is not limited toparticular sequences, expression vectors, synthetic TF, hostmicroorganisms, or processes, as such may vary. It is also to beunderstood that the terminology used herein is for purposes ofdescribing particular embodiments only, and is not intended to belimiting.

As used in the specification and the appended claims, the singular forms“a,” “an,” and “the” include plural referents unless the context clearlydictates otherwise. Thus, for example, reference to an “expressionvector” includes a single expression vector as well as a plurality ofexpression vectors, either the same (e.g., the same operon) ordifferent; reference to “cell” includes a single cell as well as aplurality of cells; and the like.

In this specification and in the claims that follow, reference will bemade to a number of terms that shall be defined to have the followingmeanings:

The terms “optional” or “optionally” as used herein mean that thesubsequently described feature or structure may or may not be present,or that the subsequently described event or circumstance may or may notoccur, and that the description includes instances where a particularfeature or structure is present and instances where the feature orstructure is absent, or instances where the event or circumstance occursand instances where it does not.

The terms “host cell” and “host microorganism” are used interchangeablyherein to refer to a living biological cell that can be transformed viainsertion of an expression vector. Thus, a host organism or cell asdescribed herein may be a prokaryotic organism (e.g., an organism of thekingdom Eubacteria) or a eukaryotic cell. As will be appreciated by oneof ordinary skill in the art, a prokaryotic cell lacks a membrane-boundnucleus, while a eukaryotic cell has a membrane-bound nucleus.

The term “heterologous DNA” as used herein refers to a polymer ofnucleic acids wherein at least one of the following is true: (a) thesequence of nucleic acids is foreign to (i.e., not naturally found in) agiven host microorganism; (b) the sequence may be naturally found in agiven host microorganism, but in an unnatural (e.g., greater thanexpected) amount; or (c) the sequence of nucleic acids comprises two ormore subsequences that are not found in the same relationship to eachother in nature. For example, regarding instance (c), a heterologousnucleic acid sequence that is recombinantly produced will have two ormore sequences from unrelated genes arranged to make a new functionalnucleic acid. Specifically, the present invention describes theintroduction of an expression vector into a host microorganism, whereinthe expression vector contains a nucleic acid sequence coding forpeptides and proteins that is not normally found in a hostmicroorganism. With reference to the host microorganism's genome, then,the nucleic acid sequence that codes for the peptides and proteins isheterologous.

The terms “expression vector” or “vector” refer to a compound and/orcomposition that transduces, transforms, or infects a hostmicroorganism, thereby causing the cell to express nucleic acids and/orproteins other than those native to the cell, or in a manner not nativeto the cell. An “expression vector” contains a sequence of nucleic acids(ordinarily RNA or DNA) to be expressed by the host microorganism.Optionally, the expression vector also comprises materials to aid inachieving entry of the nucleic acid into the host microorganism, such asa virus, liposome, protein coating, or the like. The expression vectorscontemplated for use in the present invention include those into which anucleic acid sequence can be inserted, along with any preferred orrequired operational elements. Further, the expression vector must beone that can be transferred into a host microorganism and replicatedtherein. Preferred expression vectors are plasmids, particularly thosewith restriction sites that have been well documented and that containthe operational elements preferred or required for transcription of thenucleic acid sequence. Such plasmids, as well as other expressionvectors, are well known to those of ordinary skill in the art.

The term “transduce” as used herein refers to the transfer of a sequenceof nucleic acids into a host microorganism or cell. Only when thesequence of nucleic acids becomes stably replicated by the cell does thehost microorganism or cell become “transformed.” As will be appreciatedby those of ordinary skill in the art, “transformation” may take placeeither by incorporation of the sequence of nucleic acids into thecellular genome, i.e., chromosomal integration, or by extrachromosomalintegration. In contrast, an expression vector, e.g., a virus, is“infective” when it transduces a host microorganism, replicates, and(without the benefit of any complementary virus or vector) spreadsprogeny expression vectors, e.g., viruses, of the same type as theoriginal transducing expression vector to other microorganisms, whereinthe progeny expression vectors possess the same ability to reproduce.

As used herein, the terms “nucleic acid sequence,” “sequence of nucleicacids,” and variations thereof shall be generic topolydeoxyribonucleotides (containing 2-deoxy-D-ribose), topolyribonucleotides (containing D-ribose), to any other type ofpolynucleotide that is an N-glycoside of a purine or pyrimidine base,and to other polymers containing nonnucleotidic backbones, provided thatthe polymers contain nucleobases in a configuration that allows for basepairing and base stacking, as found in DNA and RNA. Thus, these termsinclude known types of nucleic acid sequence modifications, for example,substitution of one or more of the naturally occurring nucleotides withan analog; internucleotide modifications, such as, for example, thosewith uncharged linkages (e.g., methyl phosphonates, phosphotriesters,phosphoramidates, carbamates, etc.), with negatively charged linkages(e.g., phosphorothioates, phosphorodithioates, etc.), and withpositively charged linkages (e.g., arninoalklyphosphoramidates,aminoalkylphosphotriesters); those containing pendant moieties, such as,for example, proteins (including nucleases, toxins, antibodies, signalpeptides, poly-L-lysine, etc.); those with intercalators (e.g.,acridine, psoralen, etc.); and those containing chelators (e.g., metals,radioactive metals, boron, oxidative metals, etc.). As used herein, thesymbols for nucleotides and polynucleotides are those recommended by theIUPAC-IUB Commission of Biochemical Nomenclature (Biochem. 9:4022,1970).

The term “operably linked” refers to a functional linkage between anucleic acid expression control sequence (such as a promoter) and asecond nucleic acid sequence, wherein the expression control sequencedirects transcription of the nucleic acid corresponding to the secondsequence.

Method for Constructing Synthetic Transcription Factors

The present invention provides for a synthetic transcription factor (TF)comprising a first peptide capable of binding a target ligand, a secondpeptide capable of binding a target DNA, and a peptide linker linkingthe first and second peptides. In some embodiments, the target DNA is anactivator or repressor site of a gene of interest. Depending on thetarget DNA and the gene of interest, the binding of target DNA by thesynthetic TF can either activate or repress transcription of the gene ofinterest from a target promoter.

In some embodiments, the presence of the target ligand causes thesynthetic TF to not bind the target DNA, while the absence of the targetligand causes the synthetic TF to bind the target DNA.

In some embodiments, the presence of the target ligand causes thesynthetic TF to bind the target DNA, while the absence of the targetligand causes the synthetic TF to not bind the target DNA.

In some embodiments, the first peptide is a ligand-binding domain of anatural TF, such as Idi. In some embodiments, the second peptide is aDNA-binding domain (DBD) of a natural protein, such as the DBD of AraC.

The present invention provides for a nucleic acid comprising anucleotide sequence encoding the synthetic TF of the present invention.In some embodiments, a promoter capable of transcription is operablylinked the nucleotide sequence encoding the synthetic TF. The presentinvention provides for a vector capable of stable maintenance in a hostcell comprising the nucleic acid encoding the synthetic TF. In someembodiments, the vector is an expression vector. The present inventionprovides for a host cell comprising the vector capable of stablemaintenance in a host cell comprising the nucleic acid encoding thesynthetic TF.

The present invention provides for a synthetic system for modulating theexpression of a gene of interest from a target promoter in response to atarget ligand. The synthetic system comprises the synthetic TF of thepresent invention, or a nucleic acid encoding the synthetic TF, the geneof interest, optionally the target ligand, and the necessary componentsfor transcription (and optionally translation) of the synthetic TFand/or the gene of interest. In some embodiments, the system is an invitro or cell-free system. In some embodiments, the system is an in vivosystem.

The present invention provides for a method for synthetic transcriptionfactors (TFs), and their use and construction thereof. TFs are a classof proteins that regulate transcription of one or more gene by bindingspecific DNA specific sequences^(1,2). TFs have functionally andstructurally distinct domains that perform various functions. Some ofdomains include, but are not limited to, ligand-binding domain (LBD),activation (AD), and DNA-binding domain (DBD). The LBD allows the TF tobind specific ligands, AD allows the TF to activate transcription byinteracting with RNA polymerase, and DBD allows the TF to bind specificDNA sequences, which in turn effects transcription.

Although many TFs exist in nature, a TF to bind many ligands withbiotech or medical application applications does not currently exist.The present invention provides for a method for assembling synthetic TFsthat are not naturally occurring. This method enables the constructionof biological sensors (biosensors, sensor modules) that haveapplications in metabolic engineering, gene therapy, drug delivery, stemcell engineering, anti-viral therapeutics, and the like^(3,4). A sensormodule is defined as having a target ligand, a TF that binds the targetligand, and a promoter regulated by the TF.

The present invention provides for a synthetic TF comprising 3 parts:(1) a protein or protein domain (such as LBD from a naturally occurringTF) that binds a target ligand, (2) an AD or DBD, and (3) a DNA sequencethat fuses part (1) to part (2). A schematic of the synthetic TF isprovided in FIG. 1. One requirement of the design is that aconformational change results from the binding of part (1) to the targetligand such that the synthetic TF can exist in at least two differentconformational states, one of which activates transcription from apromoter. This specification describes the construction of fourdifferent synthetic TFs for regulating two different promoters based onchanging isoprenoid concentrations in bacteria and yeast.

The AraC protein regulates expression of arabinose utilization genesfrom the promoter P_(BAD) by preferentially binding different DNAsequences in the presence and absence of arabinose⁵. AraC has a distinctligand-binding domain (LBD) and DNA-binding domain (DBD), and changesits ability to activate P_(BAD) depending on whether the LBD isarabinose bound. In some embodiments of the invention, synthetic TFs forisoprenoids are constructed by replacing AraC's LBD with proteinsdemonstrating isoprenoid binding activities, and engineered a syntheticE. coli TF (chimeric protein IA,) to respond to isopentenyl-diphosphate(IPP), the central intermediate for all isoprenoid biosynthesis⁶, byfusing AraC's DBD with IPP isomerase enzyme (idi)⁷ as the LBD. Idi wasselected, because crystallographic data suggests it dimerizes uponbinding IPP⁸, and such LBD dimerization should create at least twodifferent conformational states for IA, only one of which shouldactivate transcription. Therefore, the bacterial synthetic TF IA,consisted of idi as Part (1), AraC's DBD as Part (2), and AraC's linkeras Part (3).

IA is tested as part of a sensor module that consisted of IPP, IA, andP_(BAD) (FIG. 2) in Escherichia coli (E. coli) HC175, a variant of E.coli MG1655 capable of converting mevalonate to IPP, monitoring theoutput of the sensor module with the fluorescent protein Mcherry.Feeding HC175 different concentrations of mevalonate in the presence ofIA changed fluorescence, but no change in fluorescence was observed inthe presence of only AraC's DBD (AC) (FIG. 3). Therefore, it isconcluded that IA can regulate P_(BAD) according to changing IPPconcentrations. Variants of IA are constructed to demonstrate howtranscriptional activity could be tuned for different applications,especially medicinal ones where tight regulation is necessary. IA ismodified using error-prone PCR and isolated two mutants: IA32 showedhalf the output level, while IA44 showed twice the output level of IA(FIG. 3).

This method for assembling synthetic TFs can be generalized to otherorganisms. A synthetic TF is constructed for isoprenoids inSaccharomyces cerevisiae (S. cerevisiae). The Gal4 protein regulatesexpression of GAL genes in response to galactose⁹. Similar to AraC, thefunctional domains of Gal4 are structurally distinct, consisting of anactivator domain (AD) and DBD¹⁰. Idi is used as the LBD (Part (1)) andfused it to Gal4's AD and DBD (Part (2)s), as Idi dimerization shouldbring the AD and DBD in close enough proximity to activate transcriptionfrom a GAL promoter (e.g., P_(GAL10)). A synthetic DNA for Part (3) isdesigned. This synthetic TF is tested in a sensor module (FIG. 4)consisting of IPP, synthetic TF, and the promoter P_(GAL10), and outputfrom the sensor module is monitored with the fluorescent proteinYEcitrine in S. cerevisiae MO219, a genetically modified strain thatincreases isoprenoid production when induced with galactose¹¹. A changein fluorescence greater than baseline is observed after galactoseinduction (FIG. 5). Two additional yeast TFs were constructed fromproteins known to bind IPP (Idi1¹² and Erg20¹³) as Part (1)s in place ofIdi, and both showed even greater changes in fluorescence followinginduction. Combined with IA, these Gal4-based TFs highlight our design'smodularity in assembling synthetic TFs.

References cited in the paragraphs above under “Method for ConstructingSynthetic Transcription Factors”:

-   ¹ Price, M. N., Dehal, P. S. & Arkin, A. P., Orthologous    Transcription Factors in Bacteria Have Different Functions and    Regulate Different Genes, PLoS Computation Biology 3, 1739-1750    (2007).-   ² Farnham, P. J., Insights from genomic profiling of transcription    factors, Nature Reviews Genetics 10, 605-616 (2009).-   ³ Young, R. A., Control of the Embryonic Stem Cell State, Cell 144,    940-954 (2011).-   ⁴ Rider, T. H., et al., Broad-Spectrum Antiviral Therapeutics, PLos    ONE 6, e22572 (2011).-   ⁵ Soisson, S. M., et al., Structural Basis for Ligand-Regulated    Oligomerization of AraC, Science 276, 421-425 (1997).-   ⁶ Lange, B., et al., Isoprenoid biosynthesis: The evolution of two    ancient and distinct pathways across genomes, PNAS 97, 13172-13177    (2000).-   ⁷ Hahn, F. M., Hurlburt, A. P. & Poulter, C. D., Escherichia coli    Open Reading Frame 696 Is idi, a Nonessential Gene Encoding    Isopentenyl Diphosphate Isomerase, J. Bacteriology 181, 4499-4504    (1999).-   ⁸ De Ruyck, J., Oudjama, Y. & Wouters, J, Monoclinic form of    isopentenyl diphosphate isomerase: a case of polymorphism in    biomolecular crystals Acta. Cryst F64, 239-242 (2008).-   ⁹ Traven, A., Jelicic, B. & Sopta, M, Yeast Gal4: a transcriptional    paradigm revisited, EMBO 7, 496-499 (2006).-   ¹⁰ Fields, S. & Song, O.-k., A novel genetic system to detect    protein-protein interactions, Nature 340, 245-246 (1989).-   ¹¹ Ro, D.-K., et al., Production of the antimalarial drug precursor    artemisinic acid in engineered yeast, Nature 440, 940-943 (2006).-   ¹² Mayer, M. P., et al., Disruption and maping of IDI, the gene for    isopentenyl diphosphate isomerase in Saccharomyces cerevisiae, Yeast    8, 743-748 (1992).-   ¹³ Fischer, M. J. C., et at, Metabolic Engineering of Monoterpene    Synthesis in Yeast, Biotechnology and Bioengineering 108, 1883-1892    (2011).    Feedback-Regulated Evolution of Phenotype (FREP)

The present invention provide for a system for modulating themutagenesis frequency of a host cell. The host cell has a mutator rate(R) which is inversely proportional to a phenotypic trait (P). The hostcell comprises a sensor module and a mutator module. The sensor modulecomprises a target ligand, a TF (such as a synthetic TF) that binds thetarget ligand, and a target promoter regulated by the TF. The mutatormodule comprises the target promoter operably linked to a gene thatincreases mutation rate (mutator or mutator gene) of the host cell. Thesystem comprises a host cell comprising a synthetic TF, a target DNAwhich the binding thereof modulates the expression of the gene thatincreases mutation rate of the host cell. The target promoter isheterologous to the gene that increases mutation rate.

The present invention provides for a nucleic acid encoding a targetpromoter operably linked to a gene that can increases mutation rate(mutator or mutator gene), such as one of the mutator genes described inTable 4, wherein the target promoter has one or more activator orrepressor sites to which an activated TF (or synthetic TF) can bind, andthe target promoter is heterologous to the gene that increases mutationrate.

In some embodiments, the target ligand is a desired product that thehost cells produces. Such a host cell can be used to select for amutated host cell that is increased or maximally increased or optimizedfor its production of the desired product.

The present invention provides for a feedback-regulated evolution ofphenotype (FREP), a synthetic algorithm programming cells to increase ordecrease mutagenesis depending on the level of a particular trait. Oneuse of FREP is to evolve novel traits, which would enable engineering ofbehaviors at the microscopic (e.g., replication, differentiation) andmacroscopic (e.g., flocking, amoeba aggregation) scales observed innature, as well as novel behaviors (e.g., increased biomass degradation,metabolism of novel carbon sources, increased tolerance towards specificcompounds, increased production of target chemicals).

The algorithm accepts attenuation (A) and phenotypic diversity relatedto the target trait (P) as inputs, and outputs a mutation rate (R) (FIG.6). The logic table for FREP is described in FIG. 7. Our algorithmdictates P and R be inversely related, because enhanced mutagenesisfacilitates adaptation only when phenotypic diversity is low. Rindirectly affects P over time as beneficial mutations appear, creatinga feedback loop. A is a constraint on the maximum mutation rate andtunes P's effect on R. We implemented the novel algorithm as two modules(FIG. 8). The sensor module acts directly on the inputs and outputs atranscriptional level, which the mutator module converts into a mutationrate. The sensor module consists of three components: a ligandassociated with P, a transcription factor (TF) that binds the targetligand, and a promoter regulated by the TF. Therefore, A constrains thestrength and dynamics of the transcriptional output from the sensormodule. The mutator module is composed of a gene that increases mutationrates (mutator).

As a proof-of-concept, we implemented FREP to increase production of theindustrially-important amino acid tyrosine in Escherichia coli (E. coli)using the tyrosine-responsive TF TyrR¹ to regulate expression of themutator mutD5². In this implementation, FREP should raise R to increaseP when tyrosine concentration is low, and slow R as beneficial mutationsincreasing tyrosine production appear. We tested FREP implemented withS_(aroF3) for the sensor module and mutD5 for the mutator module in E.coli DJ238, expressing mcherry bicistronically with mutD5 to reportrelative mutator levels in the cell (FIG. 9), and isolated ten colonieswith the lowest fluorescence after 24 hours. All ten mutantsdemonstrated increased tyrosine production, and one exhibited greaterthan five-fold increase compared to the starting strain (FIG. 10).

To determine whether FREP could evolve other traits, we implemented thealgorithm to increase production of isoprenoids, a class of compoundswith a wide range of industrial applications as drugs³ and biofuels⁴, toname a few. We constructed a sensor module with IPP, the synthetictranscription factor IA44 (Example 1), and P_(BAD). We tested FREPimplemented with IA44 for evolution of increased isoprenoid productionin E. coli MG1655, and expressed mcherry bicistronically with themutator module to monitor relative mutator levels. Ten colonies with thelowest fluorescence after 24 hours were made electrocompetent andtransformed with a plasmid containing the lycopene synthase genes(pLyc). Lycopene measured from a random transformant for all tencolonies was higher than the control not modified with FREP. Sixcolonies had mutants producing on average 2900 μg/g dry cell weight.(p.p.m.) of lycopene, whereas the control produced only 1000 p.p.m.(FIG. 11).

Finally, we examined FREP in a long-term experiment by co-transformingpLyc with IPP sensor and mutD5 mutator modules into E. coli MG1655, andmonitoring lycopene production over 288 hours. We quantified lycopeneproduction every 48 hours from ten random colonies and only passaged thecolony demonstrating the highest production. After 288 hours, lycopeneproduction increased to 6800 p.p.m. using IA44, 4700 p.p.m. using IA32,and only 400 p.p.m. using AraC (FIG. 12). A control implemented withIA44 without a mutator module produced 0 p.p.m.

We successfully demonstrated the design and implementation of asynthetic algorithm programming cells to evolve new traits by decidingwhether to increase or decrease mutagenesis. Unlike existing methods toengineer metabolism^(5,6), FREP does not require a priori knowledgeabout the genetics of the trait being evolved. Distinct from directedevolution approaches requiring phenotype-specific high-throughputscreens or selections to identify high-performing mutants, FREP isolatedmutants producing more tyrosine and IPP by monitoring the algorithm'soutput with a fluorescent protein. Our work provides a foundation forassembling intelligent synthetic biological systems capable of makingdecisions by incorporating real-time information about itself and itsenvironment.

References cited in the paragraphs above under “Feedback-RegulatedEvolution of Phenotype (FREP)”:

-   1. Pittard, J., Camakaris, H. & Yang, J., The TyrR regulon,    Molecular Microbiology 55, 16-26 (2005).-   2. Schaaper, R. M., Mechanisms of mutagenesis in the Escherichia    coli mutator mutD5: Role of DNA mismatch repair, Proc. Natl. Acad.    Sci. USA 85, 8126-8130 (1988).-   3. Chang, M. C. Y. & Keasling, J. D., Production of isoprenoid    pharmaceuticals by engineered microbes, Nature Chemical Biology 2,    674-681 (2006).-   4. Keasling, J. D. & Chou, H., Metabolic engineering delivers    next-generation biofuels, Nature Biotechnology 26, 298-299 (2008).-   5. Alper, H., Miyaoku, K. & Stephanopoulos, G., Construction of    lycopene-overproducing E. coli strains by combining systematic and    combinatorial gene knockout targets, Nature Biotechnology 23,    612-616 (2005).-   6. Wang, H. H., et al., Programming cells by multiplex genome    engineering and accelerated evolution, Nature 460, 894-899 (2009).

Suitable mutator genes are provided herein in Table 4.

TABLE 4 Mutator Organism Gene Reference Escherichia mutD5 J.-P. Horst etal., Escherichia coli mutator coli genes, Trends in Microbiology 7:29-36 (1999) Bacillus mutM M. Sasaki et al., Genetic analysis ofBacillus subtilis subtilis mutator genes, J. Gen. Appl. Microbiol. 46:183-187 (2000) Pseudomonas mutS, I. Wiegand et al., Mutator genes givingrise to aeruginosa mutL decreased antibiotic susceptibility inPseudomonas aeruginosa, Antimicrobial Agents and Chemotherapy 52:3810-3813 (2008) Synechococcus mutS D. Emlyn-Jones et al.,Nitrogen-regulated sp. hypermutator strain of Synechococcus sp. for usein in vivo artificial evolution, Appl Environ Microbiol 69: 6427-6433(2003) Saccharomyces msh2 K. Drotschmann et al., Mutator phenotypes ofcerevisiae yeast strains heterozygous for mutations in the MSH2 gene,PNAS 96: 2970-2975 (1999) Saccharomyces him1 E. P. Kelberg, HIM1, a newyeast cerevisiae Saccharomyces cerevisiae gene playing a role in controlof spontaneous and induced mutagenesis, Mutat. Res. 578: 64-78 (2005)Proteins, and Nucleic Acids Encoding Thereof

All peptides and proteins described in this specification also includehomologous peptides and proteins that has a polypeptide sequence that isat least 70%, 75%, 80%, 85%, 90%, 95% or 99% identical to any one of thepeptides and proteins described in this specification or in anincorporated reference. The homologous peptides and proteins retainamino acids residues that are recognized as conserved for the peptidesand proteins for a biological function. The homologous peptides andproteins may have non-conserved amino acid residues replaced or found tobe of a different amino acid, or amino acid(s) inserted or deleted, butwhich does not affect or has insignificant effect on the biologicalactivity of the homologous peptides and proteins. Each homologouspeptide or protein has a biological activity that is identical oressentially identical to the biological activity any one of the peptideor protein described in this specification or in an incorporatedreference. The homologous peptides and proteins may be found in natureor be an engineered mutant thereof.

The nucleic acid constructs of the present invention comprise nucleicacid sequences encoding one or more of the subject peptides andproteins. The nucleic acid of the subject peptides and proteins areoperably linked to promoters and optionally control sequences such thatthe subject peptides and proteins are expressed in a host cell culturedunder suitable conditions. The promoters and control sequences arespecific for each host cell species. In some embodiments, expressionvectors comprise the nucleic acid constructs. Methods for designing andmaking nucleic acid constructs and expression vectors are well known tothose skilled in the art.

Sequences of nucleic acids encoding the subject peptides and proteinsare prepared by any suitable method known to those of ordinary skill inthe art, including, for example, direct chemical synthesis or cloning.For direct chemical synthesis, formation of a polymer of nucleic acidstypically involves sequential addition of 3′-blocked and 5′-blockednucleotide monomers to the terminal 5′-hydroxyl group of a growingnucleotide chain, wherein each addition is effected by nucleophilicattack of the terminal 5′-hydroxyl group of the growing chain on the3′-position of the added monomer, which is typically a phosphorusderivative, such as a phosphotriester, phosphoramidite, or the like.Such methodology is known to those of ordinary skill in the art and isdescribed in the pertinent texts and literature (e.g., in Matteuci etal. (1980) Tet. Lett. 521:719; U.S. Pat. Nos. 4,500,707; 5,436,327; and5,700,637). In addition, the desired sequences may be isolated fromnatural sources by splitting DNA using appropriate restriction enzymes,separating the fragments using gel electrophoresis, and thereafter,recovering the desired nucleic acid sequence from the gel via techniquesknown to those of ordinary skill in the art, such as utilization ofpolymerase chain reactions (PCR; e.g., U.S. Pat. No. 4,683,195).

Each nucleic acid sequence encoding the desired subject peptides andproteins can be incorporated into an expression vector. Incorporation ofthe individual nucleic acid sequences may be accomplished through knownmethods that include, for example, the use of restriction enzymes (suchas BamHI, EcoRI, HhaI, Xhol, XmaI, and so forth) to cleave specificsites in the expression vector, e.g., plasmid. The restriction enzymeproduces single stranded ends that may be annealed to a nucleic acidsequence having, or synthesized to have, a terminus with a sequencecomplementary to the ends of the cleaved expression vector. Annealing isperformed using an appropriate enzyme, e.g., DNA ligase. As will beappreciated by those of ordinary skill in the art, both the expressionvector and the desired nucleic acid sequence are often cleaved with thesame restriction enzyme, thereby assuring that the ends of theexpression vector and the ends of the nucleic acid sequence arecomplementary to each other. In addition, DNA linkers may be used tofacilitate linking of nucleic acids sequences into an expression vector.

A series of individual nucleic acid sequences can also be combined byutilizing methods that are known to those having ordinary skill in theart (e.g., U.S. Pat. No. 4,683,195).

For example, each of the desired nucleic acid sequences can be initiallygenerated in a separate PCR. Thereafter, specific primers are designedsuch that the ends of the PCR products contain complementary sequences.When the PCR products are mixed, denatured, and reannealed, the strandshaving the matching sequences at their 3′ ends overlap and can act asprimers for each other. Extension of this overlap by DNA polymeraseproduces a molecule in which the original sequences are “spliced”together. In this way, a series of individual nucleic acid sequences maybe “spliced” together and subsequently transduced into a hostmicroorganism simultaneously. Thus, expression of each of the pluralityof nucleic acid sequences is effected.

Individual nucleic acid sequences, or “spliced” nucleic acid sequences,are then incorporated into an expression vector. The invention is notlimited with respect to the process by which the nucleic acid sequenceis incorporated into the expression vector. Those of ordinary skill inthe art are familiar with the necessary steps for incorporating anucleic acid sequence into an expression vector. A typical expressionvector contains the desired nucleic acid sequence preceded by one ormore regulatory regions, along with a ribosome binding site, e.g., anucleotide sequence that is 3-9 nucleotides in length and located 3-11nucleotides upstream of the initiation codon in E. coli. See Shine etal. (1975) Nature 254:34 and Steitz, in Biological Regulation andDevelopment: Gene Expression (ed. R. F. Goldberger), vol. 1, p. 349,1979, Plenum Publishing, N.Y.

Regulatory regions include, for example, those regions that contain apromoter and an operator. A promoter is operably linked to the desirednucleic acid sequence, thereby initiating transcription of the nucleicacid sequence via an RNA polymerase enzyme. An operator is a sequence ofnucleic acids adjacent to the promoter, which contains a protein-bindingdomain where a repressor protein can bind. In the absence of a repressorprotein, transcription initiates through the promoter. When present, therepressor protein specific to the protein-binding domain of the operatorbinds to the operator, thereby inhibiting transcription. In this way,control of transcription is accomplished, based upon the particularregulatory regions used and the presence or absence of the correspondingrepressor protein. An example includes lactose promoters (LacI repressorprotein changes conformation when contacted with lactose, therebypreventing the Lad repressor protein from binding to the operator).Another example is the tac promoter. (See deBoer et al. (1983) Proc.Natl. Acad. Sci. USA, 80:21-25.) As will be appreciated by those ofordinary skill in the art, these and other expression vectors may beused in the present invention, and the invention is not limited in thisrespect.

Although any suitable expression vector may be used to incorporate thedesired sequences, readily available expression vectors include, withoutlimitation: plasmids, such as pSC101, pBR322, pBBR1MCS-3, pUR, pEX,pMR100, pCR4, pBAD24, pUC19; bacteriophages, such as M13 phage and λphage. Of course, such expression vectors may only be suitable forparticular host cells. One of ordinary skill in the art, however, canreadily determine through routine experimentation whether any particularexpression vector is suited for any given host cell. For example, theexpression vector can be introduced into the host cell, which is thenmonitored for viability and expression of the sequences contained in thevector. In addition, reference may be made to the relevant texts andliterature, which describe expression vectors and their suitability toany particular host cell.

The expression vectors of the invention must be introduced ortransferred into the host cell. Such methods for transferring theexpression vectors into host cells are well known to those of ordinaryskill in the art. For example, one method for transforming E. coli withan expression vector involves a calcium chloride treatment wherein theexpression vector is introduced via a calcium precipitate. Other salts,e.g., calcium phosphate, may also be used following a similar procedure.In addition, electroporation (i.e., the application of current toincrease the permeability of cells to nucleic acid sequences) may beused to transfect the host microorganism. Also, microinjection of thenucleic acid sequencers) provides the ability to transfect hostmicroorganisms. Other means, such as lipid complexes, liposomes, anddendrimers, may also be employed. Those of ordinary skill in the art cantransfect a host cell with a desired sequence using these or othermethods.

For identifying a transfected host cell, a variety of methods areavailable. For example, a culture of potentially transfected host cellsmay be separated, using a suitable dilution, into individual cells andthereafter individually grown and tested for expression of the desirednucleic acid sequence. In addition, when plasmids are used, anoften-used practice involves the selection of cells based uponantimicrobial resistance that has been conferred by genes intentionallycontained within the expression vector, such as the amp, gpt, neo, andhyg genes.

The host cell is transformed with at least one expression vector. Whenonly a single expression vector is used (without the addition of anintermediate), the vector will contain all of the nucleic acid sequencesnecessary.

Once the host cell has been transformed with the expression vector, thehost cell is allowed to grow. For microbial hosts, this process entailsculturing the cells in a suitable medium. It is important that theculture medium contain an excess carbon source, such as a sugar (e.g.,glucose) when an intermediate is not introduced. In this way, cellularproduction of aromatic amino acid ensured. When added, the intermediateis present in an excess amount in the culture medium.

Host Cells

The host cells of the present invention are genetically modified in thatheterologous nucleic acid have been introduced into the host cells, andas such the genetically modified host cells do not occur in nature. Thesuitable host cell is one capable of expressing any nucleic acidconstruct encoding one or more peptides and proteins described herein.

Any prokaryotic or eukaryotic host cell may be used in the presentmethod so long as it remains viable after being transformed with asequence of nucleic acids. Generally, although not necessarily, the hostmicroorganism is bacterial. Examples of bacterial host cells include,without limitation, those species assigned to the Escherichia,Enterobacter, Azotobacter, Erwinia, Bacillus, Pseudomonas, Klebsiella,Proteus, Salmonella, Serratia, Shigella, Rhizobia, Vitreoscilla, andParacoccus taxonomical classes. Suitable eukaryotic cells include, butare not limited to, fungal, insect or mammalian cells. Suitable fungalcells are yeast cells, such as yeast cells of the Saccharomyces andCandida genera.

REFERENCES CITED

-   1. Elena, S. F., Cooper, V. S. & Lenski, R. E., Punctuated Evolution    Caused by Selection of Rare Beneficial Mutations, Science 272,    1802-1804 (1996).-   2. Desai, M. M. & Fisher, D. S., The Balance Between Mutator and    Nonmutators in Asexual Populations, Genetics 188, 997-1014 (2011).-   3. Barrick, J. E., et al., Genome evolution and adaptation in a    long-term experiment with Escherichia coli, Nature 461, 1243-1247    (2009).-   4. Sniegowski, P. D., Gerrish, P. J. & Lenski, R. E., Evolution of    high mutation rates in experimental populations of E. coli, Nature    387, 703-705 (1997).-   5. Stich, M., Manrubia, S. C. & Lázaro, E., Variable Mutation Rates    as an Adaptive Strategy in Replicator Populations, PLoS ONE 5:    e11186 (2010).-   6. Giruad, A., et al., Costs and Benefits of High Mutation Rates:    Adaptive Evolution of Bacteria in the Mouse Gut, Science 291,    2606-2608 (2001).-   7. Loh, E., Salk, J. J. & Loeb, L. A. Optimization of DNA polymerase    mutation rates during bacterial evolution, PNAS 107, 1154-1159    (2010).-   8. Dietrich, J. A., McKee, A. E. & Keasling, J. D., High-Throughput    Metabolic Engineering: Advances in Small-Molecule Screening and    Selection, Annual Review Biochemistry 79, 563-590 (2010).-   9. Kazlauskas, R. J. & Bornscheuer, U. T., Finding better protein    engineering strategies, Nature Chemical Biology 5, 526-529 (2009).-   10. Greener, A., Callahan, M. & Jerpseth, B., An efficient random    mutagenesis technique using an E. coli mutator strain, Mol.    Biotechnol. 7, 188-195 (1997).-   11. Portnoy, V. A., Bezdan, D. & Zengler, K., Adaptive laboratory    evolution—harnessing the power of biology for metabolic engineering,    Current Opinion in Biotechnology 22, 590-594 (2011).-   12. Astrom, K. J., Adaptive Feedback Control, Proceedings of the    IEEE 75, 185-217 (1987).-   13. Juminaga, D., et al., Modular Engineering of L-Tyrosine    Production in Escherichia coli, Applied and Environmental    Microbiology 78, 89-98 (2012).-   14. Pittard, J., Camakaris, H. & Yang, J., The TyrR regulon,    Molecular Microbiology 55, 16-26 (2005).-   15. Schaaper, R. M., Mechanisms of mutagenesis in the Escherichia    coli mutator mutD5: Role of DNA mismatch repair, Proc. Natl. Acad.    Sci. USA 85, 8126-8130 (1988).-   16. Chang, M. C. Y. & Keasling, J. D., Production of isoprenoid    pharmaceuticals by engineered microbes, Nature Chemical Biology 2,    674-681 (2006).-   17. Keasling, J. D. & Chou, H., Metabolic engineering delivers    next-generation biofuels, Nature Biotechnology 26, 298-299 (2008).-   18. Soisson, S. M., et al., Structural Basis for Ligand-Regulated    Oligomerization of AraC, Science 276, 421-425 (1997).-   19. Lange, B., et al., Isoprenoid biosynthesis: The evolution of two    ancient and distinct pathways across genomes, PNAS 97, 13172-13177    (2000).-   20. Hahn, F. M., Hurlburt, A. P. & Poulter, C. D., Escherichia coli    Open Reading Frame 696 Is idi, a Nonessential Gene Encoding    Isopentenyl Diphosphate Isomerase, J. Bacteriology 181, 4499-4504    (1999).-   21. De Ruyck, J., Oudjama, Y. & Wouters, J., Monoclinic form of    isopentenyl diphosphate isomerase: a case of polymorphism in    biomolecular crystals, Acta. Cryst. F64, 239-242 (2008).-   22. Hellman, L. M. & Fried, M. G., Electrophoretic mobility shift    assay (EMSA) for detecting protein-nucleic acid interactions, Nature    Protocols 2, 1849-1861 (2007).-   23. Heyduk, T. & Heyduk, E., Molecular beacons for detecting DNA    binding proteins, Nature Biotechnology 20, 171-176 (2002).-   24. Traven, A., Jelicic, B. & Sopta, M., Yeast Gal4: a    transcriptional paradigm revisited, EMBO 7, 496-499 (2006).-   25. Fields, S. & Song, O.-k., A novel genetic system to detect    protein-protein interactions, Nature 340, 245-246 (1989).-   26. Robinson, C. R. & Sauer, R. T., Optimizing the stability of    single-chain proteins by linker length and composition mutagenesis,    PNAS 95, 5929-5934 (1998).-   27. Ro, D.-K., et al., Production of the antimalarial drug precursor    artemisinic acid in engineered yeast, Nature 440, 940-943 (2006).-   28. Mayer, M. P., et al., Disruption and mapping of IDI, the gene    for isopentenyl diphosphate isomerase in Saccharomyces cerevisiae,    Yeast 8, 743-748 (1992).-   29. Fischer, M. J. C., et al., Metabolic Engineering of Monoterpene    Synthesis in Yeast, Biotechnology and Bioengineering 108, 1883-1892    (2011).-   30. Rosche, W. A. & Foster, P. L., Determining Mutation Rates in    Bacterial Populations, Methods 20, 4-17 (2000).-   31. Alper, H., Miyaoku, K. & Stephanopoulos, G., Construction of    lycopene-overproducing E. coli strains by combining systematic and    combinatorial gene knockout targets, Nature Biotechnology 23,    612-616 (2005).-   32. Wang, H. H., et al., Programming cells by multiplex genome    engineering and accelerated evolution, Nature 460, 894-899 (2009).-   33. Young, R. A., Control of the Embryonic Stem Cell State, Cell    144, 940-954 (2011).-   34. Rider, T. H., et al., Broad-Spectrum Antiviral Therapeutics,    PLos ONE 6, e22572 (2011).

The present invention also provides for a system fortriggering/increasing the expression of silent secondary metabolitebiosynthesis gene clusters through the introduction of spontaneousgenome mutations, which can lead to the production of target molecules.The system comprises one or more of the following components: anActuator for generating mutations, a Controller for controlling the rateof mutation, and a Biosensor for detecting the synthesized targetmolecule. In some embodiments, the system is capable offeedback-regulated forced evolution (FRFE) or inducible forced evolution(IFE). Particular embodiments of each are shown in FIGS. 29 and 30. Insome embodiments, the biosensor comprises a repressor, such as a Tet^(R)repressor, which is commonly encoded by secondary metabolite geneclusters. The repressor binds the final products of the clusters-encodedbiosynthetic machineries or their precursors, and typically de-repressesexpression of the genes for export of these compounds. The presentinvention also provides for a kit comprising the various componentscomprising standard parts for construction of the system (which can becodon-tuned) where task-specific parts can be easily modified bysplicing the desired parts.

FIG. 29 shows a particular embodiment of the feedback-regulated forcedevolution (FRFE). The Actuator is mutator gene dnaQ which is clonedunder the control of a constitutive strong promoter with an upstreamoperator specific for Repressor A, such as LacI. The Controller is aRepressor A-coding gene that is under the control of anotherconstitutive strong promoter that is controlled by an operator specificfor a repressor, such as a Tet^(R)-like repressor, which is responsivefor a cognate secondary metabolite (cluster-specific). TheController-Sensor is a cluster-specific Tet^(R)-like repressor (from thetarget molecule gene cluster) and a reporter gene, such as monomeric redfluorescence protein (mRFP) genes, are under the control of constitutivepromoters, but the reporter expression is controlled via a Tet^(R)-likerepressor-responsive operator. As shown in the specific example of FIG.29, DnaQ is constitutively expressed, causing an about 1000-foldincrease in spontaneous genome mutations. Some mutations lead toincreased production of the target molecule, which then binds to thecognate Tet^(R)-like repressor. The latter dissociates from the OP1operators controlling expression of both mRFP and Repressor A.Consequently, the mRFP is expressed, allowing sorting of the cells andselection of overproducers of target molecules. At the same time, theexpression of DnaQ is down-regulated due to the expression of RepressorA, this lowering the mutation rate. Cells expressing mRFP are sortedusing any suitable means, such as Fluorescence-Assisted Cell sorting(FACS).

FIG. 30 shows a particular embodiment of the inducible forced evolution(IFE). The Actuator is mutator gene dnaQ which is cloned under thecontrol of a promoter, such as a T7 promoter. with an upstream operatorspecific for Repressor A, such as LacI. The Controller is a T7 RNApolymerase-coding gene that is under the control of a constitutivepromoter that is controlled by an operator specific for a repressor,such as a Tet^(R)-like repressor which is responsive to anhydrotetracyc1ine (aTc). The Sensor is a cluster-specific Tet^(R)-like repressor (fromthe target molecule gene cluster) and a reporter gene, such as monomericred fluorescence protein (mRFP) genes, are under the control ofconstitutive promoters, but the reporter expression is controlled via aTet^(R)-like repressor-responsive operator. As shown in the specificexample of FIG. 30, the addition of aTc induces expression of T7 RNApolymerase which in turn leads to expression of DnaQ. The latter causesan about 1000-fold increase in spontaneous genome mutations. Somemutations lead to increased production of a target molecule, which inturn binds to the cognate Tet^(R)-like repressor. The latter dissociatesfrom the OP1 operator controlling expression of mRFP. Consequently, themRFP is expressed, which allows for sorting of the cells and selectionof overproducers of the target molecule. Cells expressing mRFP aresorted using any suitable means, such as Fluorescence-Assisted Cellsorting (FACS).

In both the FRFE and IFE systems, the mRFP gene can be replaced with anantibiotic resistance gene to allow for direct selection of cells whereexpression of the antibiotic resistance gene is increased. However thiswould also depend on the phenotype of the strain in question. Forexample, many streptomycetyes are resistance to multiple antibiotics,and it may be difficult to select such strains with an appropriatemarker.

The present invention can be used to activate expression of silent geneclusters containing certain types of regulators, therebytriggering/increasing production of potentially novel secondarymetabolites. The latter may be useful in drug discovery, and parts ofactivated biosynthetic pathways may be utilized for biologicalproduction of both new and known chemicals that are currently producedfrom fossil fuel, such as petroleum.

It is to be understood that, while the invention has been described inconjunction with the preferred specific embodiments thereof, theforegoing description is intended to illustrate and not limit the scopeof the invention. Other aspects, advantages, and modifications withinthe scope of the invention will be apparent to those skilled in the artto which the invention pertains.

All patents, patent applications, and publications mentioned herein arehereby incorporated by reference in their entireties.

The invention having been described, the following examples are offeredto illustrate the subject invention by way of illustration, not by wayof limitation.

Example 1 Method for Constructing Synthetic Transcription Factors

Materials and Methods

Oligonucleotides and DNA Sequencing.

All oligonucleotides were obtained from Integrated DNA Technologies withstandard purification. Restriction sites are underlined and start codonsare in italics in the primer sequences unless otherwise indicated. DNAsequencing to confirm cloning products were performed by QuintaraBiosciences.

Strains.

EcDJ106 (BLR E. coli ΔtyrR), EcDJ166 (BLR E. coli ΔtyrR ΔpheA/LaroF[P124L] tyrA[M53I; A354V]), and EcDJ238 (MG1655 E. coli ΔtyrR) weregifts from Dr. Darmawi Juminaga. All genes and promoter sequencesamplified from the E. coli chromosome were from the strain MG1655.

Construction of pLyc.

crtE, crtI, and crtB were cloned from pT-LYCm4 (gift from Dr. AdrienneMcKee) into pBAD18-Cm using SpeI and HindIII, and following standardrestriction digest and ligation cloning protocol.

Construction of IPP Sensor Modules.

See Materials and Methods for Example 4.

Construction of tyrR Sensor Module.

P_(C) was replaced with CP20 (Jensen, P. D. & Hammer, K., The Sequenceof Spacers between the Consensus Sequences Modulates the Strength ofProkaryotic Promoters. Applied and Environmental Microbiology 64, 82-87(1998)) in pCtl-RFP-AraC with the primers 5′-ggccgctagccatgggtgagtttattcttgacagtgcggccgg gggctgatatcatagcagagtactattcaatttcacacaggaaacag aagcttggcc-3′ (SEQ ID NO:1) and5′-ggccaagcttctgtttcctgtgtgaaattgaatagtactctgctatgatatcagcccccggccgcactgtcaagaataaactcacccatggctagcggcc-3′ (SEQ ID NO:2) to make pCtl-RFP-AraC-P_(CP20). tyrR wasamplified from E. coli using the following primers: tyrR-F,5′-ggcaagcttATGCGTCTGGAAGTCTTTTGTGAA-3′ (SEQ ID NO:3); tyrR-R,5′-ggcatcgatTTACTCTTCGTTCTTCTTCTGACT-3′ (SEQ ID NO:4). The PCR productwas cloned into pCtl-RFP-AraC-P_(CP20) to make pCtl-RFP-TyrR.

The sensor module S_(aroF3) was constructed by replacing P_(BAD) withthe promoter region of aroF from E. coli using the following primers:5′-GGCGCTAGCCTTTTTCAAA GCATAGCGGATTGT-3′ (SEQ ID NO:5) and5′-GGCGAATTCGATGGCGATCCTGTTT ATGCTCGT-3′ (SEQ ID NO:6), and E274Q andN316K were made to tyrR using SOEing PCR with the following primers:tyrR-E274Q-F, 5′-CGGTCGAGAGTCAGCTGTTTGGTC-3′ (SEQ ID NO:7);tyrR-E274Q-R, 5′-GACCAAACAGCTGACTCTCGACCG-3′ (SEQ ID NO:8);tyrR-N316K-F, 5′-TGCGTTTCCTTAAAGATGGCACTT-3′ (SEQ ID NO:9);tyrR-N316K-R, 5′-AAGTGCCATCTTTAAGGAAACGCA-3′ (SEQ ID NO:10).

Characterization of tyrR Sensor Module.

S_(aroF3) was transformed into EcDJ106 and EcDJ166, and plated on LBagar with ampicillin. Clones were grown overnight in LB media withampicillin, inoculated into fresh media the next day, and tyrosineproduction was quantified after 20 hours. RFP fluorescence was measuredusing a Spectramax M2 (Molecular Devices) exciting at 495 nm andmeasuring emission at 520 nm Abs₆₀₀ was also measured using a SpectramaxM2.

Construction of FREP Vectors.

mutD was amplified from the MG1655 E. coli chromosome and cloned intopCtl-S or pCtl-RFP-S(S designates the sensor module) using the primers5′-GGCGAATTCTTTAAGAAGGAGATATACATATGA-′3 (SEQ ID NO:11) and5′-GGCGGTACCTTATGCTCGCCAGAGGCAACTTCC-3′ (SEQ ID NO:12) to make pNeg-X orpNeg-RFP-X, respectively. mutD5 was a gift from Dr. Adrienne McKee andcloned into pCtl-X or pCtl-RFP-X using the same pair of primers to makepMut-X or pMut-RFP-X, respectively.

Assessing Phenotypic Diversity after a Single Round of FREP.

MG1655 E. coli were transformed with pMut-RFP-S_(IA44). Cells wereplated on a LB agar plate with ampicillin, and grown for 1 day at 37° C.Ten mutants with the lowest RFP expression by visual inspection werepicked from the plate, inoculated into LB media with ampicillin, andgrown overnight at 37° C. Overnight cultures of each mutant wereinoculated into fresh LB media the next day to an Abs₆₀₀ of 0.05, grownto an Abs₆₀₀ of 0.4 at 37° C., and made electrocompetent. Each mutantwas transformed with pLyc, plated on a LB agar plate withchloramphenicol, and grown for 1 day at 37° C. A colony was picked fromeach plate, inoculated into LB media with chloramphenicol, and assayedfor lycopene production. The same experiment was repeated withpMut-RFP-AraC, except the transformants were plated on LB agar platewith ampicillin and 10 mM arabinose.

For tyrosine production, EcDJ238 were transformed withpMut-RFP-S_(aroF3). Cells were plated on a LB agar plate withampicillin, and grown for 1 day at 37° C. Ten mutants with the lowestRFP expression by visual inspection were picked from the plate,inoculated into LB media with ampicillin and grown for 24 h at 37° C.Each culture was assayed for tyrosine production. The experiment wasrepeated using MOPS minimal media with 0.5% glucose.

Long-Term Experiment for Increased Lycopene Production Using FREP.

MG1655 E. coli were transformed with pMut-S_(IA44) and pLyc. Cells wereplated on a LB agar plate with ampicillin and chloramphenicol, and grownfor 2 days at 37° C. Ten colonies were picked and assayed for lycopeneproduction. The colony that produced the most lycopene was passaged toevolve further, and the average of the three highest production levelsis reported. The same experiment was repeated with pMut-IA32 andpMut-AraC. For pMut-AraC, 10 mM arabinose was added to the LB agarplates with antibiotics.

Assay for Lycopene Production.

Cells were grown in LB media with chloramphenicol for 20 hours at 37° C.1 ml of culture was centrifuged at 13,000 g for 1 min, the supernatantwas removed, and the pellet was washed with 1 ml of water. 1 mL ofacetone was added to the washed pellet, and the sample was vortexed andincubated at 55° C. for 15 min. The sample was centrifuged at 13,000 gfor 1 min, and the supernatant was transferred to a cuvette and measuredwith a spectrophotometer at Abs₄₇₀. The Abs₄₇₀ data was calibrated to alycopene standard purchased from Sigma-Aldrich. The amount of lycopeneextracted from a culture was normalized to the dry cell weight (dcw)calculated from its Abs₆₀₀ (0.41 g dcw/Abs₆₀₀ (Kim, S. W., Keasling, J.D. Metabolic Engineering of the Nonmevalonate Isopentenyl DiphosphateSynthesis Pathway in Escherichia coli Enhances Lycopene Production.Biotechnology & Bioengineering 72, 408-415 (2001)).

Assay for L-Tyrosine Production.

Cells were grown in either LB or MOPS minimal media (0.5% glucose) withampicillin for 20 hours at 37° C. 500 μL of culture was centrifuged at13,000 g for 1 min, the supernatant was filtered through a 0.452 μmcentrifugal filter (VWR) and used for HPLC analysis. L-tyrosine wasmeasured using an Agilent 1200 Series HPLC system with a photodiodearray detector set at wavelengths 210, 254, and 280 nm. The samples wereseparated using a reverse phase C₁₈ column (Inertsil 2.1×250 mm, 3.5 μmfrom GL Sciences, Inc.). The following linear gradient of water (solventA) and methanol (solvent B) was used with a flow rate of 0.15 ml/min: 5%B from 0-8 min, 5-40% B from 8-13 min, hold at 40% B from 13-16 min,40-5% B from 16-21 min, and equilibrate at 5% B for 10 min L-tyrosineconcentrations were calibrated to an L-tyrosine standard purchased fromSigma-Aldrich.

Example 2 Feedback-Regulated Evolution of Phenotype (FREP)

Materials and Methods

Oligonucleotides and DNA Sequencing

All oligonucleotides were obtained from Integrated DNA Technologies withstandard purification. Restriction sites are underlined and start codonsare in italics in the primer sequences unless otherwise indicated. DNAsequencing to confirm cloning products were performed by QuintaraBiosciences.

Strains.

The kanamycin cassette was cloned from pKD4 into pMevB to make pMevB-Kanusing the following primers: 5′-GGCCCCGGGGTGTAGGCTGGAGCTGCTTC-3′ (SEQ IDNO:13) and 5′-GGCGAGCTCATGGGAATTAGCCATGGTCC-3′ (SEQ ID NO:14). EcHC175was generated by amplifying mk, pmk, and pmd of the mevalonate operonwith the kanamycin cassette from pMevB-Kan with the following primers:5′-ATCTATAATGATGAGTGATCAGAATTACATGTGAGAAATTCCAGGCTTTACACTTTAT-3′ (SEQ IDNO:15) and5′-TTACGTTATGCTCACAACCCCGGCAAATGTCGGGGTTTTTATGGGAATTAGCCATGGT-3′ (SEQ IDNO:16), and knocking out idi in MG1655 E. coli with the PCR productaccording to Datsenko & Wanner (Datsenko, K. A. & Wanner, B. L.,One-step inactivation of chromosomal genes in Escherichia coli K-12using PCR products. PNAS 97, 6640-6645 (2000)) (homology regions initalics). ScMO219 (S. cerevisiae EPY219 (Ro, D.-K., et. al., Productionof the antimalarial drug precursor artemisinic acid in engineered yeast.Nature 440, 940-943 (2006)) without pADS) was provided by Dr. MarioOuellet. All genes and promoter sequences amplified from the E. colichromosome were from the strain MG1655. All genes amplified from the S.cerevisiae chromosome were from the strain BY4742.

Construction of Sensor Modules Containing IA.

pBAD24M1 was constructed by removing HindIII from pBAD24 usingQuickChange PCR with the following primers:5′-CAGGCATGCTTGCTTGGCTGTTTT-3′ (SEQ ID NO:17) and5′-AAAACAGCCAAGCAAGCATGCCTG-3′ (SEQ ID NO:18) (where HindIII was removedis underlined). pCtl-S_(AraC) was constructed by cutting the araCregulon from pBAD24M-gfp (Lee, S. K., et al., Directed Evolution of AraCfor Improved Compatibility of Arabinose- and Lactose-InduciblePromoters. Applied and Environmental Microbiology 73, 5711-5715 (2007))using ClaI and EcoRI, and cloning it into pBAD24M1. pCtl-RFP-S_(AraC)was constructed by cloning mcherry into pCtl-S_(AraC) behind P_(BAD)using the following primers: RFP-F,5′-GGCGGTACCTTAAGTAGGGAGGTAAATACATGGTTTCCAAGGGCGAGGAG-3′ (SEQ ID NO:19);RFP-R, 5′-GGCTCTAGATTATTATTTGTACAGCTCATCCAT-3′ (SEQ ID NO:20).

IA was constructed by fusing idi to the C-terminus of araC using SOEingPCR. idi was amplified from E. coli using the following primers: idi-F,5′-GGCAAGCTTATGCAAACGGAACACGTCATT-3′ (SEQ ID NO:21); idi-SOE-R,5′-ATGGAGCGACTCGTTAATTTTAAGCTGGGTAAATGC-3′ (SEQ ID NO:22). TheC-terminus of araC was amplified from pBAD24 using the followingprimers: araC-SOE-F, 5′-ATTAACGAGTCGCTCCATCCA-3′ (SEQ ID NO:23); araC-R,5′-GGCATCGATTTATGACAACTTGACGGCTAC-3′ (SEQ ID NO:24). Those PCR productswere templates for SOEing PCR using idi-F and araC-R to amplify thefusion construct. IA was cloned into pCtl-S_(AraC), replacing AraC tomake pCtl-S_(IA), and pCtl-RFP-S_(AraC) to make pCtl-RFP-S_(IA). Mutantsof IA were generated using the GeneMorph II Random Mutagenesis Kit(Agilent Technologies) according to the manufacturer's instructions. IAmutants were cloned into pCtl-RFP using idi-F and araC-R, transformedinto EcHC1, and screened for changes in RFP expression in the presence(10 mM) and absence (0 mM) of mevalonate relative to IA. RFP wasmeasured using a Spectramax M2 (Molecular Devices) exciting at 587 nmand measuring emission at 610 nm Two mutants of interest were isolated:IA32 and IA44. pCtl-S_(Ac) and pCtl-RFP-S_(AC) were constructed byamplifying the C-terminal domain of AraC with the primers:5′-GGCAAGCTTATTAACGAGTCGCTCCATCCA-3′ (SEQ ID NO:25) and araC-R, andcloning into pCtl-S_(AraC) and pCtl-RFP-S_(AraC), respectively.

Characterization of IA Sensor Modules.

Expression of RFP from P_(BAD) controlled by one of the transcriptionfactors (AraC, AC, IA, IA32, and IA44) were determined by transformingpCtl-RFP-S(S is the sensor module with one of the transcription factors)into EcHC175 and plating on LB agar plates with ampicillin andkanamycin. Three clones were picked from each plate and grown overnightin LB media with antibiotic. Each overnight culture was inoculated intoEZ Rich Defined Media (Teknova) with antibiotic to an Abs₆₀₀ of 0.05,grown for 3 hours at 37° C., induced with IPTG (0.1 mM) and mevalonate(0-10 mM) (or 0-10 mM arabinose for AraC), and grown for an additional17 hours at 37° C. RFP fluorescence was measured using a Spectramax M2(Molecular Devices) exciting at 495 nm and measuring emission at 520 nmAbs₆₀₀ was also measured using a Spectramax M2.

Construction of Yeast Synthetic Transcription Factors.

The TEF promoter was amplified and cloned into pESC-Ura to makepESC-P_(TEF) using the primers 5′-GGCGGATCCATAGCTTCAAAATGTTTCTAC-3′ (SEQID NO:26) and 5′-GGCCCCGGGAAACTTAGATTAGATTGCTAT-3′ (SEQ ID NO:27).yEcitrine was amplified and cloned into pESC-P_(TEF) behind P_(gal10) tomake pESC-YFP-P_(TEF) using the primers5′-GGCATCGATAACATGTCTAAAGGTGAAGAATTA-3′ (SEQ ID NO:28) and5′-GGCAGATCTTTATTTGTACAATTCATCCATACC-3′ (SEQ ID NO:29). The cyc1terminator and TEF promoter were fused using SOEing PCR with thefollowing primers: 5′-GGCCTCGAGATCCGCTCTAACCGAAAAGGA-3′ (SEQ ID NO:30),5′-GTAGAAACATTTTGAAGCTATCTTCGAGCGTCCCAAAACCTT-3′ (SEQ ID NO:31),5′-AAGGTTTTGGGACGCTCGAAGATAGCTTCAAAATGTTTCTAC-3′ (SEQ ID NO:32), and5′-GGCAAGCTTAAACTTAGATTAGATTGCTATGCT-3′ (SEQ ID NO:33) to make P_(TEF2).

idi was fused to the activator and DNA binding domain of gal4,respectively, using SOEing PCR with idi being 3′ of the gal4 domains.The activator domain of gal4 was amplified from S. cerevisiae using thefollowing primers: yAD-F, 5′-GGCCCCGGGACCATGGCCAATTTTAATCAAAGTGGG-3′(SEQ ID NO:34); yAD-R,5′-ACCGGTTCCACCACCACTACCGCCTCCACTTCCGCCACCCTCTTTTTTTGGGTTTGGT GG-3′ (SEQID NO:35). The DNA binding domain of gal4 was amplified from S.cerevisiae using the following primers: yDBD-F,5′-GGCAAGCTTACCATGAAGCTACTGTCTTCTATCGAA-3′ (SEQ ID NO:36); yDBD-R,5′-ACCGGTTCCACCACCACTACCGCCTCCACTTCCGCCACCCGATACAGTCAACTGTCT TTG-3′ (SEQID NO:37). idi was amplified from E. coli using the following primers:yGI-SOE-F, 5′-AGTGGTGGTGGAACCGGTGGAGGCAGTGGTGGAGGCCAAACGGAACACGTCATTTTATTG-3′ (SEQ ID NO:38); yAD-GI-R,5′-GGCCTCGAGTTATTTAAGCTGGGTAAATGCAGA-3′ (SEQ ID NO:39); yDBD-GI-R,5′-GGCGGTACCTTATTTAAGCTGGGTAAATGCAGA-3′ (SEQ ID NO:40). The PCR productof yAD-F and yAD-R was fused to the product of yGI-SOE-F and yAD-GI-R tomake yAD-GI. The PCR product of yDBD-F and yDBD-R was fused to theproduct of yGI-SOE-F and yDBD-GI-R to make yDBD-GI. yAD-GI, P_(TEF2),and yDBD-GI were cloned into pESC-YFP-P_(TEF) behind P_(TEF) to makepESC-YFP-S_(Idi-Gal4).

idi1 was fused to the activator and DNA binding domain of gal4,respectively, using SOEing PCR with idi1 being 3′ of the gal4 domains.Idi1 was amplified from S. cerevisiae using the following primers:yGI1-SOE-F, 5′-AGTGGTGGTGGAACCGGTGGAGGCAGTGGTGGAGGCACTGCCGACAACAATAGTATG-3′ (SEQ ID NO:41); yAD-GI1-R, 5′-GGCCTCGAGTTATAGCATTCTATGAATTTGCCTG-3′(SEQ ID NO:42); yDBD-GI1-R, 5′-GGCGGTACCTTATAGCATTCTATGAATTTGCCTG-3′(SEQ ID NO:43). The PCR product of yAD-F and yAD-R was fused to theproduct of yGI1-SOE-F and yAD-GI1-R to make yAD-GI1. The PCR product ofyDBD-F and yDBD-R was fused to the product of yGI1-SOE-F and yDBD-GI1-Rto make yDBD-GI1. yAD-GI1, P_(TEF2), and yDBD-GI1 were cloned intopESC-YFP-P_(TEF) behind P_(TEF) to make pESC-YFP-S_(Idi1-Gal4).

erg20 was fused to the activator and DNA binding domain of gal4,respectively, using SOEing PCR with erg20 being 3′ of the gal4 domains.erg20 was amplified from S. cerevisiae using the following primers:yGE20-SOE-F, 5′-AGTGGTGGTGGAACCGGTGGAGGCAGTGGTGGAGGCGCTTCAGAAAAAGAAATTAGGAGA-3′ (SEQ ID NO:44); yAD-GE20-R,5′-GGCCTCGAGCTATTTGCTTCTCTTGTAAACTTT-3′ (SEQ ID NO:45); yDBD-GE20-R,5′-GGCGGTACCCTATTTGCTTCTCTTGTAAACTTT-3′ (SEQ ID NO:46). HindIII and KpnIwere removed from erg20 using the following primers:5′-GCTATCTACAAGCTATTGAAATCT-3′ (SEQ ID NO:47),5′-AGATTTCAATAGCTTGTAGATAGC-3′ (SEQ ID NO:48),5′-ACTGCTTCGGTACTCCAGAAC-3′ (SEQ ID NO:49), and5′-GTTCTGGAGTACCGAAGCAGT-3′ (SEQ ID NO:50) (where HindIII and KpnI wereremoved are underlined). The PCR product of yAD-F and yAD-R was fused tothe product of yGE20-SOE-F and yAD-GE20-R to make yAD-GE20. The PCRproduct of yDBD-F and yDBD-R was fused to the product of yGE20-SOE-F andyDBD-GE20-R to make yDBD-GE20. yAD-GE20, P_(TEF2), and yDBD-GE20 werecloned into pESC-YFP-P_(TEF) behind P_(TEF) to makepESC-YFP-S_(Erg20-Gal4).

Characterization of Yeast Synthetic Transcription Factors.

pESC-YFP-P_(TEF), pESC-YFP-P_(TEF2)-S_(Idi-Gal4),pESC-YFP-S_(Idi1-Gal4), and pESC-YFP-S_(Erg20-Gal4) were transformedinto ScMO219, and plated on SD agar-Ura plates. Plates were grown at 30°C. for 2-3 days. Three clones from each plate were grown overnight in SDmedia-Ura, inoculated into fresh media the following day, and grown for3 days at 30° C. YFP fluorescence was measured using a Spectramax M2(Molecular Devices) exciting at 516 nm and measuring emission at 529 nmAbs₆₀₀ was also measured using a Spectramax M2.

Example 3 Programming Adaptive Control to Evolve New Phenotypes

Based on theoretical and experimental data, we constructed an adaptivecontrol process mimicking adaptation by programming cells to changetheir mutation rate based on a particular phenotype. This system iscalled feedback-regulated evolution of phenotype (FREP), and isimplemented with a sensor to gauge the target phenotype and an actuatorto alter the mutation rate. To evolve certain novel traits without anyknown natural sensors, we developed a framework to assemble synthetictranscription factors and used it to construct four different sensorsthat recognize isopentenyl diphosphate in bacteria and yeast. Weverified FREP by evolving increased tyrosine and isoprenoid production.Taken together, our work demonstrates how complex behaviors could berationally engineered using control-based systems.

A method capable of regulating mutagenesis in vivo according to aparticular phenotype, independent of whether it is linked to growth,could circumvent the constraints set by transformation inefficiencies,deleterious mutations, and assay availability. We created such a methodby implementing the variable mutation rate strategy to evolve new traitsusing an adaptive control system¹² we call feedback-regulated evolutionof phenotype (FREP). FREP consists of two modules that control themutation rate of the genome (M) based on the concentration of a ligand(L) associated with the target phenotype being evolved. The actuatormodule translates a transcriptional signal (T) into M, and the sensormodule modifies T by converting L into a change in transcriptionalsignal (ΔT). M affects L over time as beneficial mutations for thetarget phenotype are generated in the genome, creating a feedback loopthat causes M to decrease as L increases. The sensor is assembled fromtwo components: a transcription factor (TF) that binds the target ligandand a promoter regulated by the TF. Depending on the target ligand, FREPcould evolve a phenotype at either the population or single-cell level.If the ligand is diffusible across the cell membrane and the rate ofdiffusion >>δL/δt, then the effect of FREP is averaged across the entirepopulation. However, if the ligand is not diffusible across the cellmembrane or its diffusion across the membrane is <<δL/δt, then FREP actson each individual cell separately. Here we demonstrate the applicationof FREP to each ligand type.

We performed FREP to increase production of the industrially-importantamino acid tyrosine¹³ in Escherichia coli using the tyrosine-responsiveTF TyrR¹⁴ to regulate expression of the mutator mutD5¹⁵. In thisimplementation, M should be high initially because tyrosineconcentration (L) is low, and M is reduced as beneficial mutations thatincrease tyrosine production appear. We modified TyrR and threeTyrR-regulated promoters (P_(aroF), P_(aroL), P_(aroP)) to constructtwenty different sensors, and screened their response to tyrosine in E.coli DJ106 and DJ166, two derivatives of BLR that produce differentamounts of tyrosine. We monitored each sensor's output with thefluorescent protein mcherry. Sensor S_(aroF3) was the most sensitive tochanges in tyrosine concentration, showing a 25% decrease influorescence from the lower to higher producing strain and a dynamicrange of 0.44 RFU/mM/OD.

We tested FREP implemented with S_(aroF3) for the sensor and mutD5 forthe actuator in E. coli DJ238, expressing mcherry bicistronically withmutD5 to monitor T and the relative mutator levels in the cell. Wereasoned that mcherry levels could decrease in response to eitherincreased tyrosine production or mutations disrupting the sensor. Weisolated ten colonies with the lowest fluorescence after 24 hours andquantified tyrosine production to distinguish between the two scenarios.All ten mutants demonstrated increased tyrosine production, and oneexhibited greater than five-fold increase compared to the startingstrain. Our observations indicate that raising M when L is low increasedtyrosine production, and increased L led to increased ΔT, consistentwith our design.

To determine whether FREP could evolve other traits, we implemented anadaptive control system to increase production of isoprenoids, a classof compounds with a wide range of industrial applications, such asdrugs¹⁶ and biofuels¹⁷. Natural TFs for these compounds have not beendiscovered yet, so we developed a framework to rationally assemblesynthetic TFs that could be used to regulate evolution towards highisoprenoid-producing strains. Our strategy was to construct syntheticTFs reminiscent of natural TFs by taking advantage of their structuraland functional modularity. The framework assembles a synthetic TFs fromthree parts: Part1 binds the target ligand, Part2 converts the bindingsignal into AT by regulating RNA polymerase binding to the targetpromoter, and Part3 joins Part1 and Part2 together.

For example, AraC regulates expression of arabinose utilization genesfrom the promoter P_(BAD) by preferentially binding different DNAsequences in the presence and absence of arabinose¹⁸. AraC has adistinct N-terminal ligand-binding domain (LBD) and C-terminalDNA-binding domain (DBD), and changes its ability to activate or repressP_(BAD) depending on whether the LBD has bound arabinose. We reasoned itshould be possible to construct synthetic TFs for isoprenoids byreplacing AraC's LBD with proteins that bind isoprenoids, and engineereda synthetic E. coli TF (chimeric protein IA) to respond to isopentenyldiphosphate (IPP), the central intermediate for all isoprenoidbiosynthesis¹⁹, by fusing the AraC DBD (Part2) and linker (Part3) withIPP isomerase (idi²⁰) (Part1). We chose Idi, because crystallographicdata indicated that it dimerizes upon binding IPP²¹, suggesting thatdimerization of Part1 should create at least two differentconformational states for IA, only one of which should activatetranscription.

A sensor consisting of IA and P_(BAD) was tested by monitoring itsoutput with mcherry in a modified strain of E. coli MG1655 able toconvert mevalonate to IPP (HC175). Titrating mevalonate from 0-10 mMchanged fluorescence by over three fold. There was no change influorescence when only the AraC DBD and linker (AC) regulated P_(BAD).We also evaluated expression from the divergent promoter (P_(C)) withcfp. Combined with the P_(BAD) data, IA appears to regulate P_(BAD) andP_(C) nearly as tightly as AraC. Unlike AraC, IA represses P_(BAD) inthe presence of ligand. Furthermore, both half-sites I₁ and I₂ upstreamof P_(BAD) are necessary but interchangeable for IA regulation. Theseobservations indicate IA can regulate T from P_(BAD) based on L (IPPconcentration) with a dynamic range of 210 RFU/mM/OD, assuming all ofthe mevalonate was converted to IPP.

We purified IA to confirm it binds the I₁ and I₂ half-sites adjacentP_(BAD) in vitro. Gel electrophoresis mobility shift assay (EMSA)²²experiments showed two bands when I₁ and I₁I₂ were substrates, and threebands when the substrate was the DNA sequence from P_(C) to P_(BAD). Theadditional band supports the observation that IA regulates both P_(BAD)and P_(C), which have distinct binding sequences. The shifted DNA bandswere less intense when IPP was added, indicating that IA's affinity forthe binding sequences decreases in the presence of IPP. We confirmedthat IPP modulates IA DNA binding using fluorescence resonance energytransfer (FRET), by splitting I₁ and I₁I₂ into two DNA fragments eachconstituting half of the original sequence and tagged with either afluorophore or quencher²³. Only the presence of IA and bothhalf-sequences induced a change in fluorescence. Adding IPP decreasedthe change in fluorescence across all concentrations of IA tested. Thus,both in vivo and in vitro data are consistent with IA regulation oftranscription from P_(BAD) according to changing IPP concentrations.

To demonstrate that our framework for assembling synthetic TFs could begeneralized to other organisms, we constructed a synthetic TF forisoprenoids in Saccharomyces cerevisiae using the GAL4 protein, whichregulates expression of GAL genes in response to galactose²⁴. Similar toAraC, the functional domains of GAL4 are structurally distinct,consisting of an activator domain (AD) and DBD²⁵. We reused Idi as Part1and fused it to the GAL4 AD and DBD (Part2), reasoning that Ididimerization should bring the AD and DBD in close enough proximity toactivate transcription from a GAL promoter (e.g., P_(GAL10)). Part3 wasa 19 amino acid sequence demonstrating relatively high stability²⁶. Thissensor was tested by monitoring its output with the fluorescent proteinyEcitrine in S. cerevisiae MO219, a genetically modified strain thatincreases isoprenoid production when induced with galactose²⁷. Weobserved a change in fluorescence greater than baseline after galactoseinduction. Two additional yeast TFs were constructed from yeast proteinsknown to bind IPP (Idi1²⁸ and Erg20²⁹) as Part1 in place of Idi, andboth showed even greater changes in fluorescence following induction.Induction led to an almost two-fold increase in sensor output inresponse to increased isoprenoid levels using the synthetic TFconstructed with Erg20. Combined with IA, these GAL4-based TFs highlightour design's modularity in assembling synthetic TFs for constructingsensors, alleviating the need to rely on pre-existing biologicalcomponents.

Next, we modified the E. coli IPP sensor to tune its dynamic range andmaximum transcriptional level (T_(max)), generating variants bymodifying IA using error-prone PCR. IA32 (L39M, S127C) showed half theT_(max) of IA and a dynamic range of 145 RFU/mM/OD, while IA44 (R267H)showed twice the T_(max) of IA and a dynamic range of 350 RFU/mM/OD. Weimplemented FREP using a sensor with one of three synthetic TFs (AC,IA32, or IA44) and the mutD5 actuator, and examined these constructs inE. coli MG1655 using Luria-Delbruck fluctuation analysis³⁰. Thirtycolonies for each implementation were tested for rifampicin resistance,an orthogonal phenotype that could be quantified quickly. In general, weobserved more rifampicin-resistant mutants with higher mutatorexpression, and a strong correlation between relative mutator expressionand mutation rate (r=0.97). For example, IA32 and IA44 exhibited afour-fold difference in T_(max) and a 2.4-fold difference in M. Anegative control consisting of a sensor with IA44 and no actuatorgenerated no rifampicin-resistant mutants. These results show thatincreasing ΔT decreases M, consistent with our design, and suggest thatdynamically controlling mutator expression changes mutation rates.

We performed FREP with IA44 for evolution to increase isoprenoidproduction in E. coli MG1655, and expressed mcherry bicistronically withthe actuator to monitor relative mutation rates. Ten colonies with thelowest fluorescence after 24 hours were made electrocompetent andtransformed with a plasmid containing the lycopene synthase genes(pLyc). Lycopene measured from a random transformant for all tencolonies was higher than the control not modified with FREP. Sixcolonies had mutants producing on average 2900 rig lycopene/g dry cellweight. (p.p.m.), a nearly three-fold increase compared to the controlthat did not undergo FREP, which produced only 1000 p.p.m. Repeating theexperiment with a sensor employing AraC as a negative control (AraC doesnot respond to IPP) generated no mutants producing more lycopene thanthe initial strain, illustrating the importance of the feedback loopbetween M and L to couple the mutation rate to the phenotype beingevolved.

Finally, we examined the ability of FREP to generate novel phenotypes inthe context of a long-term experiment. We co-transformed pLyc with anIPP sensor and mutD5 actuator into E. coli MG1655, and monitored theevolution of IPP production using lycopene over 432 hours. We quantifiedlycopene production every 72 hours from ten random colonies and onlypassaged the isolate demonstrating the highest production levels. After432 hours, lycopene production increased to 6800 p.p.m. using IA44, 4700p.p.m. using IA32, and only 400 p.p.m. using AraC. A negative FREPcontrol implemented with IA44 without an actuator produced 0 p.p.m. Forthe strains evolved using FREP implemented with IA44 and an actuator, wepurified pLyc from each time point. Transforming those plasmids into E.coli MG1655 did not lead to more lycopene production compared to theoriginal plasmid. This observation indicates that mutations generated byFREP that increase isoprenoid production reside on the chromosome andare specific to increasing IPP production. Overall, our data indicate ahigher mutation rate increased the target phenotype more, beneficialmutations generated were specific to the target trait independent of thescreen, and dynamically controlling the mutation rate evolved the targettrait faster.

We successfully designed and implemented an adaptive control processprogramming cells to evolve new phenotypes by deciding whether toincrease or decrease mutagenesis. Unlike existing methods to engineermetabolism³¹⁻³², FREP has the advantage of not requiring a prioriknowledge about the genes, RNA, proteins, and their interactions thatgovern the trait being evolved. This approach is distinct from otherdirected evolution approaches requiring phenotype-specifichigh-throughput screens or selections to identify high-performingmutants. We demonstrated the application of FREP by evolving engineeredE. coli with increased tyrosine and IPP production levels, and isolatingthe evolved strains by monitoring process output with a fluorescentprotein. Notably, we also presented a framework to rationally constructsynthetic TFs that enable the development of orthogonal sensors lesslikely to interact with existing cellular networks without being limitedto the molecular recognition properties and control functions ofnaturally-occurring TFs. More broadly, this approach to sensorengineering may have applications in anti-viral therapeutics, genetherapy, and stem cell reprogramming, where tight regulation ofcomplicated spatio-temporal intracellular interactions arenecessary^(33,34). Above all, our work provides a foundation forassembling intelligent synthetic biological systems capable ofautonomously making decisions by incorporating real-time intra- andextracellular information.

Example 4 Programming Adaptive Control to Evolve New Phenotypes

The complexity inherent in biological systems challenges efforts torationally engineer novel phenotypes, especially those not amenable tohigh-throughput screens and selections. In nature, adaptation canrapidly evolve new traits by changing the mutation rate in a cell. Basedon theory and experimental data, we constructed an adaptive controlprocess that programs cells to change their mutation rate based on aparticular desired phenotype. This system is called feedback-regulatedevolution of phenotype (FREP), and is implemented with a sensor to gaugethe target phenotype and an actuator to alter the mutation rate. Toevolve certain novel traits that have no known natural sensors, wedeveloped a framework to assemble synthetic transcription factors usingmetabolic enzymes and constructed four different sensors that recognizeisopentenyl diphosphate in bacteria and yeast. We verified FREP byevolving increased tyrosine and isoprenoid production. Taken together,our work demonstrates how complex behaviors could be rationallyengineered using control-based systems.

Adaptation is a behavior that allows cells to survive and thrive inconstantly changing environmental conditions and is characterized byrapid genetic change creating rare beneficial mutations¹. The appearanceof microbial strains with accelerated mutation rates accompany periodsof adaptation in both natural and laboratory environments^(2,3), such asin the emergence of bacterial antibiotic resistance⁴. Models andexperimental data of the adaptive process indicate a “variable mutationrate” strategy is used to evolve traits, where increased mutation ratesare only beneficial to populations with low phenotypic diversity, whilepopulations with high degrees of diversity benefit from decreasedmutation rates^(5,6).

Many mutagenesis strategies to generate diversity in the laboratoryexist, but most industrially important phenotypes are not amenable tothe high-throughput screens and selections required to isolate mutantsexhibiting the desired traits. Furthermore, directed evolutionstrategies that generate mutant libraries in vitro are limited by theligation efficiency⁸, and those that use mutator strains withunregulated, high mutation rates to generate mutant libraries in vivo⁹suffer from the accumulation of deleterious mutations that eventuallylead to cell death. Although adaptation has proven useful for evolvingcertain phenotypes, its application has been limited to traits that aredirectly tied to growth¹⁰. Therefore, a method capable of regulatingmutagenesis in vivo according to a particular phenotype, independent ofwhether it is linked to growth, could circumvent the constraints set byligation inefficiencies, deleterious mutations, and assay availability.

We created such a method by implementing the “variable mutation rate”strategy to evolve new traits using an adaptive control system we callfeedback-regulated evolution of phenotype (FREP) (FIG. 1a ). FREP is intheory analogous to the two-module genetic circuit developed by Liu etal¹¹ that dynamically controls cell motility according to cell density.Similarly, FREP consists of two modules that control the mutation rateof the genome (M) based on the concentration of a ligand (L) associatedwith the target phenotype being evolved. The actuator module converts atranscriptional signal (T) into M, and the sensor module modifies T byconverting L into a change in transcriptional signal (ΔT). M affects Lover time as beneficial mutations for the target phenotype are generatedin the genome, creating a feedback loop that causes M to decrease as Lincreases. The sensor is assembled from two components: a transcriptionfactor (TF) that binds the target ligand and a promoter regulated by theTF. Depending on the target ligand, FREP could evolve a phenotype ateither the population or single-cell level (FIG. 1b ). If the ligand isdiffusible across the cell membrane and the rate of diffusion >>dL/dt,then the effect of FREP is averaged across the entire population.However, if the ligand is not diffusible across the cell membrane or itsdiffusion across the membrane is <<dL/dt, then FREP acts on eachindividual cell separately. Here we demonstrate the application of FREPto each ligand type.

We performed FREP to increase production of the industrially importantamino acid tyrosine¹² in Escherichia coli using the tyrosine-responsiveTF TyrR¹³ to regulate expression of the mutator mutD5¹⁴ (FIG. 17). Inthis implementation, M should be high initially because the tyrosineconcentration (L) is low, and M is reduced as beneficial mutations thatincrease tyrosine production appear. We modified TyrR and threeTyrR-regulated promoters (P_(aroF), P_(aroL), P_(aroP)) to constructtwenty different sensors, and screened their response to tyrosine in E.coli DJ106 and DJ166, two derivatives of BLR that produce differentamounts of tyrosine. We monitored each sensor's output with thefluorescent protein mcherry (FIGS. 18-20). Sensor S_(aroF3) was the mostsensitive to changes in tyrosine concentration, showing a 25% decreasein fluorescence from the lower to higher producing strain and a dynamicrange of 0.44 RFU/mM/OD (FIG. 2a ).

We tested FREP implemented with S_(aroF3) for the sensor and mutD5 forthe actuator in E. coli DJ238, expressing mcherry bicistronically withmutD5 to monitor T and the relative mutator levels in the cell. Wereasoned that mcherry levels could decrease in response to eitherincreased tyrosine production or mutations disrupting the sensor ormcherry expression. We isolated ten colonies with the lowestfluorescence after 24 hours and quantified tyrosine production todistinguish between the different scenarios. All ten mutantsdemonstrated increased tyrosine production, and one exhibited greaterthan five-fold increase compared to the starting strain (FIG. 2b ). Ourobservations indicate that raising M when L (tyrosine) is low increasedtyrosine production, and the higher L increased ΔT, consistent with ourdesign.

To determine if FREP could evolve other traits, we implemented anadaptive control system to increase production of isoprenoids, a classof compounds with a wide range of industrial applications, such aspharmaceuticals¹⁵ and biofuels¹⁶. Natural TFs for these compounds havenot been discovered yet, so we developed a framework to rationallyassemble synthetic TFs that could be used to regulate evolution towardshigh isoprenoid-producing strains. Our strategy was to constructsynthetic TFs reminiscent of natural TFs by taking advantage of theirstructural and functional modularity. The framework assembles asynthetic TFs from three parts: Part1 is a metabolic enzyme that bindsthe target ligand, Part2 converts the binding signal into ΔT byregulating RNA polymerase binding to the target promoter, and Part3joins Part1 and Part2 together.

For example, AraC regulates expression of arabinose utilization genesfrom the arabinose-inducible araBAD promoter (P_(BAD)) by preferentiallybinding different DNA sequences in the presence and absence ofarabinose¹⁷. AraC has a distinct N-terminal, ligand-binding domain (LBD)and C-terminal, DNA-binding domain (DBD), and changes its ability toactivate or repress P_(BAD) depending on whether the LBD has boundarabinose. We reasoned it should be possible to construct synthetic TFsfor isoprenoids by replacing AraC's LBD with metabolic enzymes thatnaturally bind isoprenoids. We engineered a synthetic E. coli TF(chimeric protein IA, FIG. 3a ) to respond to isopentenyl diphosphate(IPP), the central intermediate for all isoprenoid biosynthesis¹⁸, byfusing the AraC DBD (Part2) and linker (Part3) with IPP isomerase(idi¹⁹) (Part1). We chose Idi, because crystallographic data indicatedthat it dimerizes upon binding IPP²⁰, suggesting that dimerization ofPart1 should create at least two, different conformational states forIA, only one of which should activate transcription.

A sensor consisting of IA and P_(BAD) was tested by monitoring itsoutput with mcherry in a modified strain of E. coli MG1655 able toconvert mevalonate to IPP (HC175). Titrating mevalonate from 0-10 mMchanged fluorescence by over three fold (FIG. 3b ). There was no changein fluorescence when a synthetic TF consisting of only the AraC DBD andlinker (AC) regulated P_(BAD). We also evaluated expression from thedivergent araC promoter (P_(C)) with cfp (Table 1). Combined with theP_(BAD) data, IA appears to regulate P_(BAD) and P_(C) nearly as tightlyas AraC. Unlike AraC, IA represses P_(BAD) in the presence of ligand.Furthermore, both half-sites I₁ and I₂ upstream of P_(BAD) are necessarybut interchangeable for IA regulation (Table 2). These observationsindicate IA can regulate T from P_(BAD) based on L (IPP concentration)with a dynamic range of 210 RFU/mM/OD, assuming all of the mevalonatewas converted to IPP.

TABLE 1 Fluorescence output from P_(BAD) and P_(C). The promotersP_(BAD) and P_(C) were regulated by one of three TFs: AC, AraC, or IA.P_(BAD) was monitored using RFP and P_(C) with CFP. Fluorescence outputwas normalized to the output from the promoters regulated by IA in theabsence of mevalonate (0 mM). Experiments were performed in HC175induced with 0.1 mM IPTG. 10 mM arabinose was added in the case of “+Inducer” for AraC, and 10 mM mevalonate was added in the cases of “+Inducer” for AC and IA. CFP RFP −Inducer +Inducer −Inducer +Inducer AC2.8 ± 0.02 1.4 ± 0.2 0.19 ± 0.03 0.11 ± 0.02 AraC 1.5 ± 0.05 0.80 ± 0.030.22 ± 0.01  1.5 ± 0.002 IA 1.0 ± 0.06 0.64 ± 0.1   1.0 ± 0.07 0.28 ±0.1 

TABLE 2 Fluorescence output from P_(BAD) with different regulatorysequences. One of four combinations of the half-sitesI₁ and I₂ (shown in bold) was used to regulate expression fromP_(BAD). Fluorescence values were normalized to the output using the wild-type I₁I₂ sequence in the absence of inducer(0 mM mevalonate). Experiments were performed in HC175induced with 0.1 mM IPTG, and 10 mM mevalonate was added in the case of “+ Inducer”. The sequences areSEQ ID NOs: 51-54, respectively. Sequence −Inducer +Inducer I₁I₁tagcatttttatccataagattagcatttttatccata 0.10 ± 0.00 0.13 ± 0.01 I₁I₂tagcatttttatccataagattagcggatcctacctga 1.00 ± 0.02 0.36 ± 0.01 I₂I₁tagcggatcctacctgaagattagcatttttatccata 1.12 ± 0.06 0.56 ± 0.01 I₂I₂tagcggatcctacctgaagattagcggatcctacctga 0.14 ± 0.01 0.11 ± 0.00

TABLE 3 Strains and plasmids in this study. Name Archive # DescriptionHC175 JBEI-4442 E. coli MG1655 Δidi::(P_(lac) mk pmk pmd kan) DJ106JBEI-4443 E. coli BLR ΔtyrR DJ166 JBEI-4444 E. coli BLR ΔtyrR ΔpheA/LaroF[P124L] tyrA[M53I; A354V] DJ238 JBEI-4445 E. coli MG1655 ΔtyrR MO219JBEI-4446 EPY219 without pADS pLyc JBEI-4447 Lycopene expression plasmidpCtl-RFP-S_(AraC) JBEI-4448 AraC sensor with RFP and mutDpCtl-RFP-S_(IA) JBEI-4449 IA sensor with RFP and mutD pCtl-RFP-S_(AC)JBEI-4450 AC sensor with RFP and mutD pCtl-RFP-S_(IA32) JBEI-4451 IA32sensor with RFP and mutD pCtl-S_(IA44) JBEI-4452 IA44 sensor with mutDpCtl-RFP-S_(IA44) JBEI-4453 IA44 sensor with RFP and mutDpCtl-RFP-S_(IA)-I1I1 JBEI-4454 IA sensor with RFP, I₁I₁, and mutDpCtl-RFP-S_(IA)-I2I1 JBEI-4455 IA sensor with RFP, I₂I₁, and mutDpCtl-RFP-S_(IA)-I2I2 JBEI-4456 IA sensor with RFP, I₂I₂, and mutDpCtl-CFP-RFP-S_(AC) JBEI-4457 AC sensor with RFP, CFP, and mutDpCtl-CFP-RFP-S_(AraC) JBEI-4458 AraC sensor with RFP, CFP, and mutDpCtl-CFP-RFP-S_(IA) JBEI-4459 IA sensor with RFP, CFP, and mutDpCtl-RFP-S_(aroF0) JBEI-4460 aroF0 sensor with RFP pCtl-RFP-S_(aroF1)JBEI-4461 aroF1 sensor with RFP pCtl-RFP-S_(aroF2) JBEI-4462 aroF2sensor with RFP pCtl-RFP-S_(aroF3) JBEI-4463 aroF3 sensor with RFPpCtl-RFP-S_(aroF4) JBEI-4464 aroF4 sensor with RFP pCtl-RFP-S_(aroF5)JBEI-4465 aroF5 sensor with RFP pCtl-RFP-S_(aroF6) JBEI-4466 aroF6sensor with RFP pCtl-RFP-S_(aroL0) JBEI-4467 aroL0 sensor with RFPpCtl-RFP-S_(aroL1) JBEI-4468 aroL1 sensor with RFP pCtl-RFP-S_(aroL2)JBEI-4469 aroL2 sensor with RFP pCtl-RFP-S_(aroL3) JBEI-4470 aroL3sensor with RFP pCtl-RFP-S_(aroL4) JBEI-4471 aroL4 sensor with RFPpCtl-RFP-S_(aroL5) JBEI-4472 aroL5 sensor with RFP pCtl-RFP-S_(aroP0)JBEI-4473 aroP0 sensor with RFP pCtl-RFP-S_(aroP1) JBEI-4474 aroP1sensor with RFP pCtl-RFP-S_(aroP2) JBEI-4475 aroP2 sensor with RFPpCtl-RFP-S_(aroP3) JBEI-4476 aroP3 sensor with RFP pCtl-RFP-S_(aroP4)JBEI-4477 aroP4 sensor with RFP pCtl-RFP-S_(aroP5) JBEI-4478 aroP5sensor with RFP pCtl-RFP-S_(aroP6) JBEI-4479 aroP6 sensor with RFPpESC-YFP-P_(TEF) JBEI-4480 Yeast expression plasmid without any sensorspESC-YFP-S_(Idi-GAL4) JBEI-4481 Idi-GAL4 sensor with YFPpESC-YFP-S_(Idi1-GAL4) JBEI-4482 Idi1-GAL4 sensor with YFPpESC-YFP-S_(Erg20-GAL4) JBEI-4483 Erg20-GAL4 sensor with YFP pPro29b-IAJBEI-4484 IA tagged with Strep-tag II pMut-S_(AC) JBEI-4485 AC sensorwith mutD5 pMut-S_(IA44) JBEI-4486 IA44 sensor with mutD5 pMut-S_(IA32)JBEI-4487 IA32 sensor with mutD5 pMut-S_(AraC) JBEI-4488 AraC sensorwith mutD5 pMut-RFP-S_(IA44) JBEI-4489 IA44 sensor with mutD5 and RFPpMut-RFP-S_(AraC) JBEI-4490 AraC sensor with mutD5 and RFPpMut-RFP-S_(aroF3) JBEI-4491 aroF3 sensor with mutD5 and RFP HC229JBEI-4492 E. coli undergoing FREP using IA44 with pLyc after 72 hrsHC230 JBEI-4493 E. coli undergoing FREP using IA44 with pLyc after 144hrs HC231 JBEI-4494 E. coli undergoing FREP using IA44 with pLyc after216 hrs HC232 JBEI-4495 E. coli undergoing FREP using IA44 with pLycafter 288 hrs HC233 JBEI-4496 E. coli undergoing FREP using IA44 withpLyc after 360 hrs HC234 JBEI-4497 E. coli undergoing FREP using IA44with pLyc after 432 hrs

We purified IA to confirm it binds the I₁ and I₂ half-sites adjacent toP_(BAD) in vitro. Gel electrophoresis mobility shift assay (EMSA²¹)experiments showed two bands when I₁ and I₁I₂ were substrates, and threebands when the substrate was the DNA sequence from P_(C) to P_(BAD)(FIG. 21). The additional band supports the observation that IAregulates both P_(BAD) and P_(C), which have distinct binding sequences.The shifted DNA bands were less intense when IPP was added, indicatingthat IA's affinity for the binding sequences decreases in the presenceof IPP. We confirmed that IPP modulates IA DNA binding usingfluorescence resonance energy transfer (FRET) by splitting I₁ and I₁I₂into two DNA fragments each constituting half of the original sequenceand tagged with either a fluorophore or quencher²². Only the presence ofIA and both half-sequences induced a change in fluorescence (FIG. 22).Adding IPP decreased the change in fluorescence across allconcentrations of IA tested (FIG. 23). Thus, both in vivo and in vitrodata are consistent with IA regulation of transcription from P_(BAD)according to changing IPP concentrations, and both I₁ and I₂ half-sitesare necessary for this regulation.

To further evaluate our framework for assembling synthetic TFs, weconstructed a synthetic TF for isoprenoids in Saccharomyces cerevisiaeusing the GAL4 protein, which regulates expression of GAL genes inresponse to galactose²³. Similar to AraC, the functional domains of GAL4are structurally distinct, consisting of an activator domain (AD) andDBD²⁴. We reused Idi as Part1 and fused it to the GAL4 AD and DBD(Part2), reasoning that Idi dimerization should bring the AD and DBD inclose enough proximity to activate transcription from a GAL promoter(e.g., P_(GAL10)). Part3 was a 19-amino acid sequence having relativelyhigh stability²⁵. This sensor (FIG. 3c ) was tested by monitoring itsoutput with the fluorescent protein yEcitrine in S. cerevisiae MO219, agenetically modified strain that increases isoprenoid production wheninduced with galactose²⁶. We observed a change in fluorescence greaterthan baseline after galactose induction (FIG. 3d ). Two additional yeastTFs were constructed from yeast enzymes known to catalyze reactions withIPP as a substrate (Idi1²⁷ and Erg20²⁸) as Part1 in place of Idi, andboth showed even greater changes in fluorescence following induction.Induction led to an almost two-fold increase in sensor output inresponse to increased isoprenoid levels using the synthetic TFconstructed with Erg20. Combined with IA, these GAL4-based TFs highlightthe modularity of our framework in assembling synthetic TFs forconstructing sensors, alleviating the need to rely on pre-existingbiological components.

Next, we modified the E. coli IPP TF IA using error-prone PCR to createIPP sensors with different dynamic ranges and maximum transcriptionlevels (T_(max)). Out of the 60 variants screened (FIG. 24), IA32 (L39M,S127C) showed half the T_(max) of IA and a dynamic range of 145RFU/mM/OD, while IA44 (R267H) showed twice the T_(max) of IA and adynamic range of 350 RFU/mM/OD (FIG. 3C). We implemented FREP using oneof three synthetic TFs (AC, IA32, or IA44) as part of the sensor and themutD5 actuator, and examined these constructs in E. coli MG1655 usingLuria-Delbruck fluctuation analysis²⁹. Thirty colonies for eachimplementation were tested for rifampicin resistance, an orthogonalphenotype that could be quantified quickly. In general, we observed morerifampicin-resistant mutants with higher mutator expression, and astrong correlation between relative mutator expression and mutation rate(r=0.97) (FIG. 25). For example, IA32 and IA44 exhibited a four-folddifference in T. and a 2.4-fold difference in M. A negative controlconsisting of a sensor with IA44 and no actuator generated norifampicin-resistant mutants. These results show that increasing ATdecreases M, consistent with our design, and suggest that dynamicallycontrolling mutator expression changes mutation rates. Furthermore, theability to adjust the dynamic range of the TF allows the targetproduction level evolved using FREP to be controlled.

We performed FREP with IA44 to increase isoprenoid production in E. coliMG1655, and expressed mcherry bicistronically with the actuator tomonitor relative mutation rates. Ten colonies with the lowestfluorescence after 24 hours were made electrocompetent and transformedwith a plasmid containing the lycopene synthase genes (pLyc). Lycopenemeasured from a random transformant for all ten colonies was higher thanthe control not modified with FREP. Six colonies had mutants producingon average 2900 rig lycopene/g dry cell weight (p.p.m.), a nearlythree-fold increase compared to the control that did not undergo FREP,which produced only 1000 p.p.m. (FIG. 26). Repeating the experiment witha sensor employing AraC as a negative control (AraC does not respond toIPP) generated no mutants producing more lycopene than the initialstrain, illustrating the importance of the feedback loop between M and Lto couple the mutation rate to the phenotype being evolved.

Finally, we examined the ability of FREP to generate novel phenotypes inthe context of a long-term experiment. We co-transformed pLyc with anIPP sensor and mutD5 actuator into E. coli MG1655, and monitored theevolution of IPP production using lycopene as a reporter over 432 hours.We quantified lycopene production every 72 hours from ten randomcolonies and only passaged the isolate demonstrating the highestproduction levels. After 432 hours, lycopene production increased to6800 p.p.m. using IA44, 4700 p.p.m. using IA32, and only 400 p.p.m.using AraC (FIG. 4). A negative FREP control implemented with IA44without an actuator produced 0 p.p.m. For the strains evolved using FREPimplemented with IA44 and an actuator, we purified pLyc from each timepoint. Transforming those plasmids into E. coli MG1655 did not lead tomore lycopene production compared to the original plasmid (FIG. 27).This observation indicates that mutations generated by FREP thatincrease isoprenoid production reside on the chromosome and are specificto increasing IPP production. Overall, our data demonstrate thatdynamical control of the mutation rate evolved a particular phenotypefaster than either the absence of or static control of the mutationrate, and the beneficial mutations generated by the dynamic controlprocess are specific to the desired phenotype.

We successfully designed and implemented an adaptive control processcapable of regulating the mutation rate by gauging the degree to which astrain exhibits a desired phenotype. Although the current implementationof FREP appears slower than certain alternative strategies forengineering metabolism^(30,31), FREP is unique because it has theadvantage of evolving a trait without a priori knowledge about thegenes, RNA, proteins, and their interactions that govern the trait beingengineered. We demonstrated the application of FREP by evolving E. colito increase tyrosine and IPP production, and isolating the evolvedstrains by monitoring the actuator level with a fluorescent protein. Weconfirmed that FREP was able to evolve phenotypes for target ligandsthat are permeable (tyrosine) and for those that are impermeable (IPP)to the cell membrane. Once the level of a target trait saturates using aparticular TF, its dynamic range could be altered to enable furtherincreases in the level of the trait using FREP. Additionally, wepresented a framework to rationally construct synthetic TFs usingmetabolic enzymes that enable the development of orthogonal sensors lesslikely to interact with existing cellular networks without being limitedto the molecular recognition properties and control functions ofnaturally occurring TFs. Above all, our work provides a foundation forassembling intelligent, synthetic biological systems capable ofautonomously making decisions by incorporating real-time, intra- andextracellular information.

Methods

Oligonucleotides and DNA Sequencing

All oligonucleotides were obtained from Integrated DNA Technologies andare presented in FIG. 28. DNA sequencing was performed by QuintaraBiosciences.

Strains and Plasmids Availability

Strains, plasmids, and plasmid sequences (in Genbank format) aredeposited in the private instance of the JBEI registry and will be movedto the public instance (webpage at:public-registry.jbei.org) afterpublication. Strains and plasmids are available from Addgene (webpageat:addgene.org), and listed in Table 3.

Strains

We cloned the kanamycin cassette from pKD4 into pMevB³² to constructpMevB-Kan using the primers Kan-F and Kan-R. We engineered EcHC175 byamplifying mk, pmk, and pmd of the mevalonate operon with the kanamycinecassette from pMevB-Kan with the primers IdiKO-F and IdiKO-R, andknocking out idi in E. coli MG1655 with the PCR product according toDatsenko & Wanner³³ . E. coli DJ106, DJ166, and DJ238 were gifts fromDr. Darmawi Juminaga. S. cerevisiae MO219 was a gift from Dr. MarioOuellet. Genes and promoter sequences amplified from the E. colichromosome were from MG1655. Genes amplified from the S. cerevisiaechromosome were from BY4742.

Construction of pLyc

We cloned crtE, crtI, and crtB from pT-LYCm4 (gift from Dr. AdrienneMcKee) into pBAD18-Cm using the restriction enzymes SpeI and HindIIIfollowing standard restriction digest and ligation cloning protocols.

Construction of Plasmids Containing E. coli IPP Sensor Modules

pCtl-RFP-S_(AraC) (S_(AraC): sensor containing AraC) was constructed byremoving HindIII from pBAD24 using QuickChange PCR with the primersDelHindIII-F and DelHindIII-R, cloning in the DNA sequence from araC toP_(BAD) from pBAD24M-gfp³⁴ using ClaI and EcoRI, cloning in mutDamplified from E. coli using the primers MutD-F and MutD-R, and cloningin mcherry using the primers RFP-F and RFP-R 3′ of the araBAD promoter,P_(BAD).

The chimeric protein IA was constructed by fusing idi to the C-terminusof araC using SOEing PCR. idi was amplified from E. coli using theprimers Idi-F and Idi-SOE-R, and the linker and C-terminus of araC wereamplified from pBAD24 using the primers AraC-SOE-F and AraC-R. These twoPCR products were templates for SOEing PCR using Idi-F and AraC-R toamplify the chimeric protein. We cloned IA into pCtl-RFP-S_(AraC) byreplacing AraC to make pCtl-RFP-S_(IA).

Mutants of IA were generated using the GeneMorph II Random MutagenesisKit (Agilent Technologies) according to the manufacturer's instructions.We cloned the IA mutants into pCtl-RFP-S_(IA) using Idi-F and AraC-R,transformed the constructs into EcHC175, and screened for changes in RFPexpression relative to IA in the presence (10 mM) and absence (0 mM) ofmevalonate with 0.1 mM isopropyl β-D-1-thiogalactopyranoside (IPTG)(Sigma-Aldrich). RFP was measured using a Spectramax M2 (MolecularDevices) exciting at 587 nm and measuring emission at 610 nm We isolatedtwo mutants: IA32 and IA44. pCtl-RFP-S_(Ac) was constructed byamplifying the C-terminal domain of AraC with the primers AC-F andAraC-R, and cloning into pCtl-RFP-S_(AraC). pCtl-RFP-S_(IA44) wasdigested with ClaI and KpnI, and the fragment containing IA44 to mutDwas cloned into pBAD24 to construct pCtl-S_(IA44).

Construction of Plasmids Containing mutD5 Mutator Module

The mutator mutD5 was a gift from Dr. Adrienne McKee and cloned intopCtl-S_(IA44), pCtl-RFP-S_(AraC), pCtl-RFP-S_(IA44), andpCtl-RFP-S_(aroF3) using the primers MutD-F and MutD-R to makepMut-S_(IA44), pMut-RFP-S_(AraC), pMut-RFP-S_(IA44), andpMut-RFP-S_(aroF3). pMut-S_(AC), pMut-S_(AraC), pMut-S_(IA32) wereconstructed by cutting the transcription factor (TF) frompCtl-RFP-S_(Ac), pCtl-RFP-S_(AraC), pCtl-RFP-S_(IA32) using ClaI andHindIII, and cloning the fragments into pMut-S_(IA44).

Characterization of E. coli IPP Sensor Modules

We measured expression of RFP from P_(BAD) controlled by one of the TFs(AraC, AC, IA, IA32, or IA44) by transforming pCtl-RFP-S(S designates asensor with one of the TFs) into EcHC175 and plating on LB agar plateswith ampicillin and kanamycin. We picked three clones from each plate,grew each clone in LB medium with antibiotics overnight, and inoculatedeach culture into fresh EZ Rich Defined Medium (Teknova) withantibiotics to an initial Abs₆₀₀ of 0.05 the following day. Each freshculture was grown for 3 hours at 37° C., induced with IPTG (0.1 mM) andmevalonate (0-10 mM) (or 0-10 mM arabinose for AraC), and grown for anadditional 17 hours at 37° C. We measured RFP fluorescence exciting at495 nm and measuring emission at 520 nm, and Abs₆₀₀ using a SpectramaxM2.

To determine IA's binding sequence upstream of P_(BAD), we amplifiedI_(L)I_(I) using the primer I1I1-F, I₂I₁ using the primer I2I1-F, orI₂I₂ using the primer I2I2-F, all paired with AraReg-R and usingpCtl-RFP-S_(IA) as template. The PCR products were cloned intopCtl-RFP-S_(IA) to replace the I₁I₂ sequence to makepCtl-RFP-S_(IA)-I₁I₁, pCtl-RFP-S_(IA)-I₂I₁, and pCtl-RFP-S_(IA)-I₂I₁.RFP expression from the modified binding sequences was determined asdescribed above.

We amplified CFP using the primers CFP-F and CFP-R, and inserted it 3′of the TF expressed 3′ of P_(C) into pCtl-RFP-S_(AC), pCtl-RFP-S_(AraC),and pCtl-RFP-S_(IA) to make pCtl-CFP-RFP-S_(Ac), pCtl-CFP-RFP-S_(AraC),and pCtl-CFP-RFP-S_(IA). RFP and CFP expression from these constructswere determined as indicated above, and CFP fluorescence was measuredusing a Spectramax M2 exciting at 433 nm and measuring emission at 475nm

Construction of Plasmids Containing Tyrosine Sensor Modules

We replaced P_(C) with CP20³⁵ in pCtl-RFP-S_(AraC) using the primersCP20-F and CP20-R, and cloned in tyrR amplified from E. coli using theprimers TyrR-F and TyrR-R to construct pCtl-RFP-TyrR.

pCtl-RFP-S_(aroF0) was constructed by amplifying the promoter region ofaroF from E. coli using the primers AroF0-F and AroF0-R, and cloning thePCR product into pCtl-RFP-TyrR to replace P_(BAD). pCtl-RFP-S_(aroF1)was constructed by mutating TyrR with the primers TyrR-E274Q-F andTyrR-E274Q-R to make TyrR E274Q³⁶, and cloning the PCR product intopCtl-RFP-S_(aroF0). pCtl-RFP-S_(aroF2) was constructed by mutating TyrRwith the primers TyrR-N316K-F and TyrR-N316K-R to make TyrR N316K³⁷, andcloning the PCR product into pCtl-RFP-S_(aroF0). pCtl-RFP-S_(aroF3) wasconstructed by mutating TyrR E274Q with the primers TyrR-N316K-F andTyrR-N316K-R, and cloning the PCR product into pCtl-RFP-S_(aroF0). TheN-terminus of TyrR was also truncated to different lengths to generateTyrR Δ43, TyrR Δ93, and TyrR Δ187³⁸. pCtl-RFP-S_(aroF4) was constructedby amplifying TyrR with the primers Del43TyrR-F and TyrR-R, and cloningthe PCR product into pCtl-RFP-S_(aroF0). pCtl-RFP-S_(aroF5) wasconstructed by amplifying TyrR with the primers Del93TyrR-F and TyrR-R,and cloning the PCR product into pCtl-RFP-S_(aroF0). pCtl-RFP-S_(aroF6)was constructed by amplifying TyrR with the primers Del187TyrR-F andTyrR-R, and cloning the PCR product into pCtl-RFP-S_(aroF0).

pCtl-RFP-S_(aroL0) was constructed by replacing P_(BAD) with thepromoter region of aroL from E. coli using the primers AroL0-F andAroL0-R, and cloning the PCR product into pCtl-RFP-TyrR. TyrR frompCtl-RFP-S_(aroF1), pCtl-RFP-S_(aroF2), and pCtl-RFP-S_(aroF3) wereamplified using the primers TyrR-F and TyrR-R and cloned intopCtl-RFP-S_(aroL0) to construct pCtl-RFP-S_(aroL1), pCtl-RFP-S_(aroL2),and pCtl-RFP-S_(aroL3), respectively. The TyrR boxes 1, 2, 3 of thepromoter P_(araL) were also modified to tune TyrR regulation of thepromoter³⁹. pCtl-RFP-S_(aroL4) was constructed by modifying thesequences of box 1 and 2 of P_(aroL) in pCtl-RFP-S_(aroL0) with theprimers AroLBox1 and 2-F and AroLBox1 and 2-R. pCtl-RFP-S_(aroL5) wasconstructed by modifying the box 3 sequence of P_(aroL) inpCtl-RFP-S_(aroL0) with the primers AroLBox3-F and AroLBox3-R.

pCtl-RFP-S_(aroP0) was constructed by replacing P_(BAD) with thepromoter region of aroP from E. coli using the primers AroP0-F andAroP0-R, and cloning the PCR product into pCtl-RFP-TyrR. TyrR frompCtl-RFP-S_(aroF1), pCtl-RFP-S_(aroF2), and pCtl-RFP-S_(aroF3) wereamplified using the primers TyrR-F and TyrR-R and cloned intopCtl-RFP-S_(aroP0) to construct pCtl-RFP-S_(aroP1), pCtl-RFP-S_(aroP2),and pCtl-RFP-S_(aroP3), respectively. pCtl-RFP-S_(aroP4) was constructedby modifying the P₂ sequence of P_(aroP) to make P_(2up) ⁴⁰ inpCtl-RFP-S_(aroP0) with the primers P2UP-F and P2UP-R.pCtl-RFP-S_(aroP5) and pCtl-RFP-S_(aroP6) were constructed by amplifyingTyrRΔ43 and TyrRΔ93 from pCtl-RFP-S_(aroF4) and pCtl-RFP-S_(aroF5),respectively, using the primers Del43TyrR-F or Del93TyrR-F paired withTyrR-R, and cloning the PCR products into pCtl-RFP-S_(aroP4).

Characterization of Tyrosine Sensor Modules

Plasmids containing each of the twenty tyrosine sensors described abovewere transformed into E. coli DJ106 and DJ166, and plated on LB agarwith ampicillin. Clones were grown overnight in LB medium withampicillin, inoculated into EZ Rich Defined Medium the next day to aninitial Abs₆₀₀ of 0.05, and tyrosine production was quantified after 20hours. RFP fluorescence and Abs₆₀₀ were measured as described earlier.The experiment was repeated in triplicate for S_(aroF3), S_(aroL5), andS_(aroP6).

Construction of Yeast Synthetic Transcription Factors and IPP SensorModules

The TEF promoter was amplified and cloned into pESC-Ura to makepESC-P_(TEF) using the primers TEF-F and TEF-R. yEcitrine was amplifiedand cloned into pESC-P_(TEF) behind P_(gal10) to make pESC-YFP-P_(TEF)using the primers YEcitrine-F and YEcitrine-R. The cyc1 terminator andTEF promoter were fused using SOEing PCR with the primers CYC1-SOE-F,CYC1-SOE-R, TEF-SOE-F, and TEF-SOE-R to make the PCR product P_(TEF2).

idi was fused to the activator and DNA-binding domains of gal4,respectively, using SOEing PCR with idi being 3′ of the gal4 domains.The activator domain of gal4 was amplified from S. cerevisiae using theprimers AD-F and AD-SOE-R. The DNA binding domain of gal4 was amplifiedusing the following primers: DBD-F and DBD-SOE-R. The AD-SOE-R andDBD-SOE-R primers included the linker sequence joining the domains toidi. idi was amplified from E. coli using the primers GI-SOE-F withAD-GI-R or GI-SOE-F with DBD-GI-R. The PCR product of AD-F and AD-SOE-Rwas fused to the product of GI-SOE-F and AD-GI-R to make AD-GI. The PCRproduct of DBD-F and DBD-SOE-R was fused to the product of GI-SOE-F andDBD-GI-R to make DBD-GI. AD-GI, P_(TEF2), and DBD-GI were cloned intopESC-YFP-P_(TEF) behind P_(TEF) to make pESC-YFP-S_(Idi-GAL4).

idi1 was fused to the activator and DNA binding domains of gal4,respectively, using SOEing PCR with idi1 being 3′ of the gal4 domains.Idi1 was amplified from S. cerevisiae using the primers GI1-SOE-F andAD-GI1-R or GI1-SOE-F and DBD-GI1-R. The PCR product of AD-F andAD-SOE-R was fused to the product of GI1-SOE-F and AD-GI1-R to makeAD-GI1. The PCR product of DBD-F and DBD-SOE-R was fused to the productof GI1-SOE-F and DBD-GI1-R to make DBD-GI1. AD-GI1, P_(TEF2), andDBD-GI1 were cloned into pESC-YFP-P_(TEF) behind P_(TEF) to makepESC-YFP-S_(Idi1-GAL4).

erg20 was fused to the activator and DNA binding domains of gal4,respectively, using SOEing PCR with erg20 being 3′ of the gal4 domains.erg20 was amplified from S. cerevisiae using the primers GE20-SOE-F withAD-GE20-R or GE20-SOE-F with DBD-GE20-R. HindIII and KpnI were removedfrom erg20 using the primers DelHindIII-Erg20-F, DelHindIII-Erg20-R,DelKpnI-Erg20-F, and DelKpnI-Erg20-R (where HindIII and KpnI wereremoved are underlined). The PCR product of AD-F and AD-SOE-R was fusedto the product of GE20-SOE-F and AD-GE20-R to make AD-GE20. The PCRproduct of DBD-F and DBD-SOE-R was fused to the product of GE20-SOE-Fand DBD-GE20-R to make DBD-GE20. AD-GE20, P_(TEF2), and DBD-GE20 werecloned into pESC-YFP-P_(TEF) 3′ of P_(TEF) to makepESC-YFP-S_(Erg20-GAL4).

Characterization of Yeast IPP Sensor Modules

pESC-YFP-P_(TEF), pESC-YFP-S_(Idi-GAL4), pESC-YFP-S_(Idi1-GAL4), andpESC-YFP-S_(Erg20-GAL4) were transformed into ScMO219 usingelectroporation, plated on Synthetic Defined (SD) agar without uraciland with 2% glucose, and grown at 30° C. for 3 days. SD medium wascomposed of 1×CSM without the appropriate amino acids (Sunrise ScienceProducts) and 1× Difco Yeast Nitrogen Base without amino acids (BD),prepared according to the manufacturers' instructions. Three clones fromeach plate were grown overnight in SD medium without uracil and with 2%glucose, inoculated into fresh medium without uracil and with 1.8%galactose and 0.2% glucose the following day to an initial Abs₆₀₀ of0.05, and grown for 3 days at 30° C. YFP fluorescence was measured usinga Spectramax M2 (Molecular Devices) exciting at 516 nm and measuringemission at 529 nm, and normalized to OD measured at 600 nm

Protein Purification of IA

We amplified IA tagged with Strep-tag II on the C-terminus using theprimers IA-StrepII-F and IA-StrepII-R, and cloned the PCR product intopPro29b⁴¹ after the promoter P_(prpB) to make pPro29b-IA. BLR(DE3) E.coli was transformed with pPro29b-IA, and an overnight culture wasinoculated into a liter of LB medium with ampicillin to an initialAbs₆₀₀ of 0.05. We grew the culture at 37° C. until the Abs₆₀₀ reached0.6, induced it with 20 mM propionate, and grew it overnight at 20° C.The cells were pelleted, resuspended in binding buffer (20 mM sodiumphosphate, 280 nM NaCl, 6 mM potassium chloride, pH 7.4), sonicated, andcentrifuged. The tagged protein was purified from the supernatant with agravity flow column using StrepTactin Sepharose High Performance (GEHealthcare) following the manufacturer's instructions. Proteinconcentration was determined using the Pierce BCA Protein Assay Kit(Thermo Scientific).

Gel Electrophoresis Mobility Shift Assay (EMSA)

The region from the promoters P_(C) to P_(BAD) was amplified frompCtl-RFP-S_(AraC) using the primers EMSA-AraReg-F and EMSA-AraReg-R. I₁of the region between P_(C) and P_(BAD) was synthesized using theprimers EMSA-I1-F and EMSA-I1-R. I₁I₂ of the region between P_(C) andP_(BAD) was synthesized using the primers EMSA-I1I2-F and EMSA-I1I2-R.Cy5 indicates that the primer was labeled with the Cy5 fluorophore (FIG.28). DNA duplexes were synthesized from the primers by mixing the pairsof oligonucleotides at 10 μM concentration in Phusion HF PCR buffer (NewEngland BioLabs), heating for 1 min at 95° C., and cooling to 25° C.over 1 hour. We incubated purified IA (0-10 nM) with Cy5 labeled DNAduplexes (20 nM) in binding buffer (10 mM Tris-HCl, 1 mM EDTA, 100 mMKCl, 1 mM dithioerythritol, 5% glycerol, pH 7.4) at room temperature(20° C.±2° C.) for 20 min. 10 μM IPP was added to test its effect on IAbinding to DNA. Samples were prepared and run on a 6% DNA retardationgel (Invitrogen) according to the manufacturer's instructions. Gels wereviewed using MultiImage III (Alpha Innotech) equipped with a Cy5 filter.

FRET DNA Binding Assay

I₁ of the region between the promoters P_(C) and P_(BAD) was synthesizedusing the primers: I1-1F, I1-2F, I1-3R, and I1-4R. FL indicates that theprimer was labeled with 6-FAM fluorescein fluorophore, and BQ indicatesthat the primer was labeled with Black Hole Quencher 1. Two pairs ofduplexes were synthesized from the primers: I₁-FL from pairing I₁-1F andI₁-4R, and I₁-BQ from pairing I₁-2F and I1-3R. We synthesized DNAduplexes from the primers by mixing each pair of oligonucleotides at 10μM concentration in Phusion HF PCR buffer, heating for 1 min at 95° C.,and cooling to 25° C. over 1 hour. A negative control duplex I₁-NC wassynthesized using unlabeled I₁-3R.

IA's ability to bind I₁ was determined by incubating purified IA (0-20nM) with I₁-FL (100 nM) and I₁-BQ (125 nM) in binding buffer (10 mMTris-HCl, pH 7.4, 1 mM EDTA, 100 mM KCl, 1 mM dithioerythritol, 5%glycerol) at room temperature (20° C.±2° C.) for 15 min Fluorescencemeasurements were made with a Spectramax M2 (Molecular Devices) excitingat 495 nm and measuring emission at 520 nm. The experiment was performedin triplicate.

We synthesized I₁I₂ DNA duplexes using the primers I1I2-1F, I1I2-2F,I1I2-3R, and I1I2-4R. An unlabeled I1I2-3R primer was used to synthesizea negative control duplex. IA's ability to bind I₁I₂ was determined asdescribed above. IPP (500 nM) was added to test its effect on IA bindingto I₁I₂. The experiment was performed in triplicate.

Luria-Delbruck Fluctuation Analysis

We transformed E. coli MG1655 with pMut-S_(IA44), and grew differentdilutions of the transformation on LB agar plates with ampicillin for 1day at 37° C. Thirty colonies were picked and resuspended in 100 μl ofwater. 50 μl of each sample was plated on a LB agar plate with 100 μg/mlrifampicin, and 50 μl for six colonies was serially diluted and platedon LB agar plates. The plates were incubated overnight at 37° C.Colonies on each plate were counted using an automated colony countingsoftware provided with the Biospectrum Multispectral Imaging System(Ultra-Violet Products Ltd.). Mutation rates were calculated usingFALCOR⁴² with the “MSS Maximum Likelihood Estimator” setting. Theexperiment was repeated with pMut-S_(AC), pMut-S_(IA32), pNeg-S_(IA44).

Assessing Phenotypic Distribution after 24 Hours of FREP

For evolving increased IPP production, we transformed E. coli MG1655with pMut-RFP-S_(IA44), and grew different dilutions of thetransformation on a LB agar plate with ampicillin for 1 day at 37° C.Ten mutants with the lowest RFP expression by visual inspection werepicked, inoculated into LB medium with ampicillin, and grown overnightat 37° C. Overnight cultures of each mutant were inoculated into freshLB medium the next day to an Abs₆₀₀ of 0.05, grown to an Abs₆₀₀ of 0.4at 37° C., made electrocompetent, transformed with pLyc, plated on a LBagar plate with chloramphenicol, and grown for 1 day at 37° C. We pickeda colony from each plate, inoculated it into LB medium withchloramphenicol, and assayed it for lycopene production. The sameexperiment was repeated with pMut-RFP-S_(AraC), except 10 mM arabinosewas added to the LB agar plates and medium.

For evolution of increased tyrosine production, we transformed DJ238with pMut-RFP-S_(aroF3), plated on a LB agar plate with ampicillin, andgrew the transformants for 1 day at 37° C. Ten mutants with the lowestRFP expression by visual inspection were picked from the plate,inoculated into MOPS minimal medium with 0.5% glucose and ampicillin,and grown for 24 h at 37° C. Each culture was assayed for tyrosineproduction.

Long-Term Experiment for Increased Lycopene Production Using FREP

E. coli MG1655 were transformed with pMut-S_(IA44) and pLyc. Cells wereplated on a LB agar plate with ampicillin and chloramphenicol, and grownfor 2 days at 37° C. We picked ten colonies and assayed each forlycopene production. The colony that produced the most lycopene waspassaged to evolve further, and the average of the three highestproduction levels is reported. A total of 6 passages was performed toevolve over 432 hours. The same experiment was repeated withpMut-S_(IA32) and pMut-S_(AraC). 10 mM arabinose was added to the LBagar plates with antibiotics for pMut-S_(AraC).

Assay for Lycopene Production

Cells were grown in LB medium with antibiotics for 20 hours at 37° C. Wecentrifuged 1 ml of culture at 13,000×g for 1 min, removed thesupernatant, and washed the pellet with 1 ml of water. 1 mL of acetonewas added to the washed pellet, and the sample was vortexed andincubated at 55° C. for 15 min. We centrifuged the sample at 13,000×gfor 1 min, transferred the supernatant to a cuvette, and measured theabsorbance at 470 nm with a spectrophotometer. The Abs₄₇₀ data wascalibrated to a lycopene standard purchased from Sigma-Aldrich. Theamount of lycopene extracted from a culture was normalized to the drycell weight (dcw) calculated from the Abs₆₀₀ (0.41 g dcw/Abs₆₀₀ ⁴³).

Assay for L-Tyrosine Production

Cells were grown in either LB or MOPS minimal medium with 0.5% glucoseand antibiotics for 20 hours at 37° C. 500 μL of culture was centrifugedat 13,000×g for 1 min, the supernatant was filtered through a 0.452 μmcentrifugal filter (VWR) and used for HPLC analysis. L-tyrosine datawere quantified using HPLC and verified using LC-MS as describedelsewhere¹³. L-tyrosine concentrations were calibrated to standardspurchased from Sigma-Aldrich.

CITED REFERENCES

-   1. Elena, S. F., Cooper, V. S. & Lenski, R. E. Punctuated evolution    caused by selection of rare beneficial mutations. Science 272,    1802-1804 (1996).-   2. Desai, M. M & Fisher, D. S. The balance between mutator and    nonmutators in asexual populations. Genetics 188, 997-1014 (2011).-   3. Sniegowski, P. D., Gerrish, P. J. & Lenski, R. E. Evolution of    high mutation rates in experimental populations of E. coli. Nature    387, 703-705 (1997).-   4. Zhang, Q. et al. Acceleration of Emergence of Bacterial    Antibiotic Resistance in Connected Microenvironments. Science 333,    1764-1767 (2011).-   5. Stich, M., Manrubia, S. C. & Lázaro, E. Variable Mutation Rates    as an Adaptive Strategy in Replicator Populations. PLoS ONE 5:    e11186 (2010).-   6. Giruad, A. et al. Costs and benefits of high mutation rates:    adaptive evolution of bacteria in the mouse gut. Science 291,    2606-2608 (2001).-   7. Dietrich, J. A., McKee, A. E. & Keasling, J. D. High-throughput    metabolic engineering: advances in small-molecule screening and    selection. Annual Review Biochemistry 79, 563-590 (2010).-   8. Hibbert, E. G. et al. Directed evolution of biocatalytic    processes. Biomol. Eng. 22, 11-19 (2005).-   9. Greener, A., Callahan, M. & Jerpseth, B. An efficient random    mutagenesis technique using an E. coli mutator strain. Molecular    Biotechnology 7, 188-195 (1997).-   10. Portnoy, V. A., Bezdan, D. & Zengler, K. Adaptive laboratory    evolution—harnessing the power of biology for metabolic engineering.    Current Opinion in Biotechnology 22, 590-594 (2011).-   11. Liu, C. et al. Sequential establishment of stripe patterns in an    expanding cell population. Science 334, 238-241 (2011).-   12. Juminaga, D. et al. Modular engineering of L-tyrosine production    in Escherichia coli. Applied and Environmental Microbiology 78,    89-98 (2012).-   13. Pittard, J., Camakaris, H., & Yang, J. The TyrR regulon.    Molecular Microbiology 55, 16-26 (2005).-   14. Schaaper, R. M. Mechanisms of mutagenesis in the Escherichia    coli mutator mutD5: role of DNA mismatch repair. Proc. Natl. Acad.    Sci. USA 85, 8126-8130 (1988).-   15. Chang, M. C. Y. & Keasling, J. D. Production of isoprenoid    pharmaceuticals by engineered microbes. Nature Chemical Biology 2,    674-681 (2006).-   16. Keasling, J. D. & Chou, H. Metabolic engineering delivers    next-generation biofuels. Nature Biotechnology 26, 298-299 (2008).-   17. Soisson, S. M., MacDougall-Shackleton, B., Schleif, R. &    Wolberger, C. Structural basis for ligand-regulated oligomerization    of AraC. Science 276, 421-425 (1997).-   18. Lange, B. M., Rujan, T., Martin, W. & Croteau, R. Isoprenoid    biosynthesis: the evolution of two ancient and distinct pathways    across genomes. Proc. Natl. Acad. Sci. USA 97, 13172-13177 (2000).-   19. Hahn, F. M., Hurlburt, A. P. & Poulter, C. D. Escherichia coli    open reading frame 696 is idi, a nonessential gene encoding    isopentenyl diphosphate isomerase. Journal of Bacteriology 181,    4499-4504 (1999).-   20. De Ruyck, J., Oudjama, Y. & Wouters, J. Monoclinic form of    isopentenyl diphosphate isomerase: a case of polymorphism in    biomolecular crystals. Acta. Cryst. F64, 239-242 (2008).-   21. Hellman, L. M. & Fried, M. G. Electrophoretic mobility shift    assay (EMSA) for detecting protein-nucleic acid interactions. Nature    Protocols 2, 1849-1861 (2007).-   22. Heyduk, T. & Heyduk, E. Molecular beacons for detecting DNA    binding proteins. Nature Biotechnology 20, 171-176 (2002).-   23. Traven, A., Jelicic, B. & Sopta, M. Yeast Gal4: a    transcriptional paradigm revisited. EMBO 7, 496-499 (2006).-   24. Fields, S. & Song, O.-k. A novel genetic system to detect    protein-protein interactions. Nature 340, 245-246 (1989).-   25. Robinson, C. R. & Sauer, R. T. Optimizing the stability of    single-chain proteins by linker length and composition mutagenesis.    Proc. Natl. Acad. Sci. USA 95, 5929-5934 (1998).-   26. D.-K. Ro et al. Production of the antimalarial drug precursor    artemisinic acid in engineered yeast. Nature 440, 940-943 (2006).-   27. Mayer, M. P., Hahn, F. M., Stillman, D. J. & Poulter, C. D.    Disruption and mapping of IDI, the gene for isopentenyl diphosphate    isomerase in Saccharomyces cerevisiae. Yeast 8, 743-748 (1992).-   28. Fischer, M. J., Meyer, S., Claudel, P., Bergdoll, M. & Karst, F.    Metabolic engineering of monoterpene synthesis in yeast.    Biotechnology and Bioengineering 108, 1883-1892 (2011).-   29. Rosche, W. A. & Foster, P. L. Determining Mutation Rates in    Bacterial Populations. Methods 20, 4-17 (2000).-   30. Alper, H., Miyaoku, K., Stephanopoulos, G. Construction of    lycopene-overproducing E. coli strains by combining systematic and    combinatorial gene knockout targets. Nature Biotechnology 23,    612-616 (2005).-   31. Wang, H. H. et al. Programming cells by multiplex genome    engineering and accelerated evolution. Nature 460, 894-899 (2009).-   32. Martin, V. J. et al. Engineering a mevalonate pathway in    Escherichia coli for production of terpenoids. Nature Biotechnology    7, 796-802 (2003).-   33. Datsenko, K. A. & Wanner, B. L. One-step inactivation of    chromosomal genes in Escherichia coli K-12 using PCR products. Proc.    Natl. Acad. Sci. USA 97, 6640-6645 (2000).-   34. Lee, S. K. et al. Directed evolution of AraC for improved    compatibility of arabinose- and lactose-inducible promoters. Applied    and Environmental Microbiology 73, 5711-5715 (2007).-   35. Jensen, P. D. & Hammer, K. The sequence of spacers between the    consensus sequences modulates the strength of prokaryotic promoters.    Applied and Environmental Microbiology 64, 82-87 (1998).-   36. Kwok, T., Yang, J., Pittard, A. J., Wilson, T. J. &    Davidson, B. E. Analysis of an Escherichia coli mutant TyrR protein    with impaired capacity for tyrosine mediated repression, but still    able to activate at sigma 70 promoters. Molecular Microbiology 17,    471-481 (1995).-   37. Koyanagi, T., Katayama, T., Suzuki, H. & Kumagai, H. Altered    oligomerization properties of N316 mutants of Escherichia coli TyrR.    Journal of Bacteriology 190, 8238-8243 (2008).-   38. Cui, J. & Somerville, R. L. Mutational uncoupling of the    transcriptional activation function of the TyrR protein of    Escherichia coli K-12 from the repression function. Journal of    Bacteriology 175, 303-306 (1993).-   39. Lawley, B. & Pittard, A. J. Regulation of aroL expression by    TyrR protein and Trp repressor in Escherichia coli K-12. Journal of    Bacteriology 176, 6921-6930 (1994).-   40. Yang, J., Wang, P. & Pittard, A. J. Mechanism of repression of    the aroP P2 promoter by the TyrR protein of Escherichia coli.    Journal of Bacteriology 181, 6411-6418 (1999).-   41. Lee, S. K. & Keasling, J. D. Heterologous protein production in    Escherichia coli using the propionate-inducible pPro system by    conventional and auto-induction methods. Protein Expression and    Purification 61, 197-203 (2008).-   42. Hall, B. M., Ma, C. X., Liang, P. & Singh, K. K. Fluctuation    AnaLysis CalculatOR: a web tool for the determination of mutation    rate using Luria-Delbrück fluctuation analysis. Bioinformatics 25,    1564-1565 (2009).-   43. Kim, S. W. & Keasling, J. D. Metabolic engineering of the    nonmevalonate isopentenyl diphosphate synthesis pathway in    Escherichia coli enhances lycopene production. Biotechnology &    Bioengineering 72, 408-415 (2001).

While the present invention has been described with reference to thespecific embodiments thereof, it should be understood by those skilledin the art that various changes may be made and equivalents may besubstituted without departing from the true spirit and scope of theinvention. In addition, many modifications may be made to adapt aparticular situation, material, composition of matter, process, processstep or steps, to the objective, spirit and scope of the presentinvention. All such modifications are intended to be within the scope ofthe claims appended hereto.

We claim:
 1. A system for modulating mutagenesis frequency of a hostcell, comprising a host cell comprising: (a) a synthetic transcriptionfactor (TF) comprising a first peptide capable of binding a targetligand, a second peptide capable of binding a target DNA, and a peptidelinker linking the first and second peptides, wherein the first peptideand the second peptide are from different proteins, and (b) a mutatormodule comprising a target promoter operably linked to a gene that iscapable of increasing a mutation rate of the host cell; wherein the hostcell has a mutator rate (R) which is inversely proportional to aphenotypic trait (P); wherein the first peptide is a ligand-bindingdomain of Idi, Idi1 or Erg20, and P is isoprenoid or lycopeneproduction, and (i) the second peptide is a DNA-binding domain (DBD) ofAraC and the target promoter is an araBAD promoter and the host cell isa prokaryotic cell, or (ii) the second peptide is a DNA-binding domain(DBD) of Gal4 and the target promoter is a GAL promoter and the hostcell is a yeast cell.
 2. The system of claim 1 wherein the host cellcomprises a nucleic acid comprising a nucleotide sequence encoding thesynthetic TF.
 3. The system of claim 2 wherein the host cell comprises avector capable of stable maintenance of the nucleic acid.
 4. The systemof claim 3 wherein the vector is an expression vector.
 5. The system ofclaim 1, wherein (i) when the host cell is a prokaryotic cell the genethat is capable of increasing a mutation rate of the host cell isEscherichia coli mutD5, Bacillus subtilis mutM, Pseudomona aeruginosamutS, Pseudomonas aeruginosa mutL, or Synechococcus sp. mutS, and (ii)when the host cell is a yeast cell the gene that is capable ofincreasing a mutation rate of the host cell is Saccharomyces cerevisiaemsh2, or Saccharomyces cerevisiae him1.
 6. The system of claim 1,wherein the first peptide is a ligand-binding domain of Idi and thesecond peptide is a DNA-binding domain (DBD) of AraC and the targetpromoter is the araBAD promoter or the second peptide is a DNA-bindingdomain (DBD) of Gal4 and the target promoter is a GAL promoter.
 7. Thesystem of claim 6, wherein the GAL promoter is P_(GAL10).
 8. The systemof claim 1, wherein the first peptide is a ligand-binding domain of Idi,Idi1 or Erg20, and the second peptide is a DNA-binding domain (DBD) ofGal4 and the target promoter is a GAL promoter.
 9. The system of claim8, wherein the GAL promoter is P_(GAL10).
 10. The system of claim 1,wherein the host cell is a prokaryotic cell which is a species ofEscherichia, Enterobacter, Azotobacter, Erwinia, Bacillus, Pseudomonas,Klebsiella, Proteus, Salmonella, Serratia, Shigella, Rhizobia,Vitreoscilla, or Paracoccus.
 11. The system of claim 10, wherein theprokaryotic cell is a species of Escherichia.
 12. The system of claim11, wherein the prokaryotic cell is Escherichia coli.
 13. The system ofclaim 1, wherein the host cell is a yeast cell which is a species ofSaccharomyces or Candida.
 14. The system of claim 13, wherein the yeastcell is a species of Saccharomyces.
 15. The system of claim 14, whereinthe yeast cell is Saccharomyces cerevisiae.